INTRODUCTION
============

Yellow fever is an arbovirus of the *Flavivirus* genus from the family *Flaviviridae* . In urban transmission cycle, *Aedes aegypti* is its main vector. In its wild type, it is a zoonosis transmitted in the American continent by vectors *Haemagogus* and *Sabethes* ^[@B1]^ . Its severe form is characterized by serious liver injury, with liver and kidney failure that can lead to death. Vaccination is the most important preventive measure^[@B3]^ .

The disease is endemic and enzootic in several tropical regions in the Americas and Africa, with periodic outbreaks. In Brazil, cases were described as endemic, particularly in the Amazon region, with sporadic outbreaks outside this area^[@B3]^ .

In December 2016, the virus reemerged in the Southeast region in Brazil, starting the largest outbreak of wild yellow fever in recent decades in the country, with 779 cases confirmed in humans in the monitoring period from July 2016 to June 2017, when 262 deaths were reported (lethality rate of 33.6%). The four states of the Southeast region -- Minas Gerais (MG), Espírito Santo (ES), Sao Paulo (SP), and Rio de Janeiro (RJ) -- reported the highest number of cases. This region has large urban centers with many sites of high density of *Aedes aegypti* infestation, and a large part of local population was not vaccinated against the disease^[@B3]\ ,\ [@B4]^ .

From July 2017 to May 16, 2018, another major outbreak occurred in the country, with 1,266 cases confirmed in humans and 415 deaths (lethality rate of 32.8%), especially in MG, SP, and RJ^[@B6]^ . Deaths were also reported in non-human primates in other Brazilian states, highlighting the importance of adopting measures to reduce the risk of disease reurbanization, including expansion of recommended vaccination areas and fractional dose campaigns^[@B3]\ ,\ [@B7]^ .

In 2018, according to data of July 5, 2018 from the Rio de Janeiro State Secretary of Health (SES/RJ), 264 cases were confirmed in 32 municipalities, with 85 deaths (32.2%); 13 locations had confirmed epizootic disease, with deaths of monkeys^[@B8]^ .

In RJ, the *Instituto Estadual de Infectologia São Sebastião* (IEISS -- São Sebastião State Institute of Infectious Diseases), an institute that has been a historical reference for treating infectious diseases, was incorporated into the *Hospital Federal dos Servidores do Estado* (HFSE) on August 20, 2012. The HFSE is a federal general-teaching hospital, which is part of the national network called *Rede de Vigilância Epidemiológica Hospitalar de Interesse Nacional* ^[@B9]^ . In this context of yellow fever outbreak, this structure of HFSE/IEISS played an important role in providing care to severe cases, hospitalizing 52 patients from March 11, 2017 to June 15, 2018. This study aimed to describe the clinical and epidemiological profile of these cases and the factors associated with death.

METHODS
=======

This study was conducted in a reference hospital for infectious diseases in Rio de Janeiro; it offers an epidemiology service that is part of the national network, which actively searches the cases treated in that unit^[@B9]^ . Rio de Janeiro boards the states of MG, ES and SP, and the Atlantic Ocean, covering 43,781,588 km^2^. It has 92 municipalities and 16,718,956 inhabitants (according to 2017 data), 96.7% of them living in urban areas^[@B10]^ . About 30% of the state area is covered by the Atlantic Forest^[@B11]^ .

From March 11, 2017 to June 15, 2018, 68 cases of suspected yellow fever were reported to the HFSE/IEISS, according to the definition of epidemiological surveillance: "individual with acute fever (up to seven days) of sudden onset, accompanied by jaundice or bleeding, who lives in or has visited a risk area for yellow fever or sites with confirmed epizootic disease in non-human primates or virus isolation in mosquito vectors for the past 15 days, not vaccinated against yellow fever or presenting unknown vaccination status"^[@B1]\ ,\ [@B2]^ . Of these, 52 cases were confirmed and hospitalized (43 in 2018), constituting the study sample. The disease was confirmed by polymerase chain reaction (PCR) test in 51 cases, and one case was confirmed by epidemiological link^[@B1]\ ,\ [@B2]^ .

This is a retrospective observational study with analysis of secondary databases of the HFSE epidemiological surveillance system from Sinan -- disease reporting system, and complementary data collection from clinical records by the epidemiology service team during the epidemiological investigation process. Demographic, epidemiological, clinical and laboratory variables were analyzed in a spreadsheet-based database exported from Sinan and complemented by typing additional variables to those existing in the investigation form for yellow fever^[@B2]\ ,\ [@B12]^ , corresponding to signs, symptoms and laboratory tests (detailed in [Table 1](#t1){ref-type="table"} and [Table 2](#t2){ref-type="table"}).

Table 1Profile of 52 confirmed cases of yellow fever whose patients were hospitalized in HFSE/IEISS. Rio de Janeiro, RJ, Brazil, March 11, 2017 to June 15, 2018.Clinical dataf%Male4586.5Age (years)  13--341223.135--491426.950--591325.060--751325.0Fever4790.4Jaundice4586.5Nausea/vomiting3669.2Headache2853.8Changes in renal excretion (oliguria, anuria or both)2853.8Bleeding2650.0Abdominal pain2548.1Myalgia1732.7Prostration/asthenia1426.9Diarrhea917.3Choluria917.3Arthralgia611.5Seizures611.5Retro-orbital pain23.8Articular edema23.8Rash11.9Faget sign11.9Conjunctival hyperemia11.9Thrombocytopenia \< 100,000/mm^3^4586.5Leucopenia3465.4Comorbidity (at least one)2038.5Arterial hypertension1019.2Alcoholism917.3Diabetes59.6Smoking47.7Hepatic steatosis23.8Rheumatoid arthritis23.8Epidemiological history and conclusion of investigation  Presence of *Aedes aegypti* in the region5198.1Epizootic diseases in the municipality of patient's residence3567.3Vaccinated against yellow fever917.3Final classification as wild yellow fever52100.0Laboratory confirmation criterion (PCR)5198.1Autochthonous case of the municipality of patient's residence3465.4Occupational disease1019.2Outcome  Death due to wild yellow fever2140.4Healed patient3159.6HFSE/IEISS: *Hospital Federal dos Servidores do Estado* / *Instituto Estadual de Infectologia São Sebastião* ; PCR: polymerase chain reaction.

Table 2Distribution of serum values of some exams according to the evolution of confirmed cases of yellow fever admitted to HFSE/IEISS. Rio de Janeiro, RJ, Brazil, March 11, 2017 to June 15, 2018.Serum valuesTotal casesDeathNon-deathMann-Whitney test (p)nMedian (min.--max.)nMedian (min.--max.)nMedian (min.--max.)Max. AST (U/L)504,833 (69--12,970)198,460 (1,803--12,970)311,820 (69--10,900)0.000Max. ALT (U/L)512,920 (86--8,064)205,379 (1,943--8,064)311,581(86--5,428)0.000Max. TB (mg/dL)525.62 (0,70--38.00)217.00 (2.00--38.00)314.23 (0.70--29.00)0.063Max. DB (mg/dL)514.03 (0.09--20.00)215.00 (2.00--20.00)303.07 (0.09--17.00)0.043Max. urea (mg/dL)4954 (15--180)2093 (45--161)2936 (15--180)0.000Max. creatinine (mg/dL)521.72 (0.7--17.5)213.2 (0.80--11.7)311.2 (0.7--17.5)0.000Min. platelet (per mm^3^)5250,000 (10,000--232,000)2138,000 (10,000--26,000)3168,000 (15,000--232,000)0.008Min. hematocrit (%)5036.0 (12.9--51.6)2029.5 (13.2--51.6)3038.5 (12.9--50.0)0.081HFSE/IEISS: *Hospital Federal dos Servidores do Estado* / *Instituto Estadual de Infectologia São Sebastião* ; AST: aspartate aminotransferase; ALT: alanine aminotransferase; TB: total bilirubin; DB: direct bilirubin.

Statistical analysis was performed in SPSS v.18 software, including descriptive statistical analysis and a bivariate and multivariate analysis by logistic regression to study the association of independent variables with the outcome of death. Odds ratio (OR) with 95% confidence intervals (95%CI) was used to estimate the chance of death.

In bivariate analysis, Pearson's chi-square test or Fisher's exact test was used for categorical variables, and Mann-Whitney test for continuous variables, with p value \< 0.05 considered statistically significant. K-means clustering analysis was used to identify the cutoff point for numerical variables corresponding to laboratory test results; it consists of dividing data into a predefined number of clusters. This type of analysis is used when there is no *a priori* hypothesis about the structure or behavior of data; it constitutes a non-hierarchical cluster by partition. Data from each continuous variable were divided into two clusters, starting with the identification of minimum and maximum values recorded. At the end of the process, a cutoff point was obtained between the mean of the maximum value of the first cluster and the minimum value of the second cluster.

In the analysis by logistic regression, variables associated with death in the previous bivariate analysis, with p \< 0.10, were included, as well as those variables considered of clinical importance (such as age, sex, comorbidity, and abdominal pain) or of interest (such as year the disease was reported). The Wald test analyzed the significance of independent variables included in the study. For global adjustment analysis, the likelihood ratio test (-2 log likelihood) was used. The agreement between probabilities predicted by the models and the responses obtained were analyzed using the Hosmer-Lemeshow test.

This study was included in a project approved by the HFSE Research Ethics Committee (protocol CEP-HFSE 000.534 of July 14, 2014).

RESULTS
=======

[Figure 1](#f01){ref-type="fig"} shows the temporal distribution of cases by epidemiological week of disease reporting; 35 (78.8%) occurred from January to March 2018. Of these, 45 (86.5%) were male patients and seven (13.5%) were female patients, aged 13 to 75 years (median 49.5 years). Self-reported race or skin color was white in 29 (55.8%), brown in 15 (28.8%), black in seven (13.5%), and yellow in one case (1.9%); 27 patients had incomplete basic education (73.0%; excluding 15 of unknown education).

Figure 1Distribution according to epidemiological week for reporting of confirmed cases of yellow fever admitted to the *Hospital Federal dos Servidores do Estado/Instituto Estadual de Infectologia São Sebastião* . Rio de Janeiro, RJ, Brazil, March 11, 2017 to June 15, 2018.

Yellow fever cases were reported in 18 municipalities of RJ, 50 residents and two Chilean tourists. In 2018, 21 patients came from the tourist region of Costa Verde, 18 from Baía de Ilha Grande (16 residents and the two Chilean tourists). The area of residence or accommodation was rural in 32 (61.5%), urban in 11 (21.2%), peri-urban in two (3.8%), and unknown in seven (13.5%) cases. Rural workers prevailed (21 cases; 40.4%); three patients were from tourism (two tourists and one guide).

[Table 1](#t1){ref-type="table"} shows the profile of cases according to clinical and epidemiological variables, and the conclusion of the epidemiological investigation. The most frequent signs and symptoms were fever (90.4%), jaundice (86.5%), and nausea and vomiting (69.2%). Changes in renal excretion (oliguria or anuria) occurred in 53.8%, bleeding in 50.0%, and abdominal pain in 48.1% of the cases. Thrombocytopenia \< 100,000/mm^3^ occurred in 86.5% and leukopenia in 65.4% of the cases.

At least one comorbidity was described in 38.5% of the cases; the most frequent ones were: systemic arterial hypertension (19.2% of cases), alcoholism (17.3%), and diabetes (9.6%). *Aedes aegypti* was reported in 98.1% of the cases in an urban area where the patient visited. Epizootic diseases in non-human primates were reported in the place of residence in 67.3% of the patients.

Nine cases (17.5%) reported history of previous vaccination against yellow fever; the period between the vaccination date and the onset of symptoms was up to four days in five patients; between 11 and 12 days in two patients; seven years in one patient; and one patient was vaccinated on the third day after symptom onset. In cases of recent vaccination, wild-type virus was confirmed by sequencing, ruling out any post-vaccination adverse event.

In 65.4% of the cases, the transmission was autochthonous of the municipality of residence; in the other cases, it was unknown, due to travels to other municipalities in the state. In 19.2%, the occupational bond was well characterized ( [Table 1](#t1){ref-type="table"} ). Regarding disease progression, 21 cases (40.4%) died (19 in 2018 and 2 in 2017).

The period between symptom onset and admission to HFSE/IEISS ranged from one to 15 days, median of 5 days, with similar periods when comparing cases leading and not leading to death. The time between symptom onset and death ranged from four to 22 days, median of 9 days. Hospitalization period ranged from one to 56 days, median of 10 days, with no significant difference when comparing cases of death (1 to 26 days; median = 11) and survivors (3 to 56 days; median = 10). The period between admission and case being reported to the epidemiological surveillance system ranged from zero to three days, median of one; 86.5% were reported up to 24 hours after admission.

[Table 2](#t2){ref-type="table"} shows the distribution of maximum serum values of aspartate aminotransferase (AST), alanine aminotransferase (ALT), total bilirubin (TB), direct bilirubin (DB), urea, creatinine, and the lower values of platelet count and hematocrit for the group of cases and according to the outcome of death. A significant association was observed between higher AST, ALT, DB, urea, and creatinine values and death, and between lower values of platelet count and death.

According to [Table 3](#t3){ref-type="table"} , the presence of the following signs and symptoms was significantly associated with a higher chance of death: jaundice, bleeding, changes in renal excretion, and seizures. Leukopenia was significantly associated with lower lethality. The cutoff points for AST, ALT, urea, and creatinine were identified by K-means analysis, which defined two clusters (1 and 2) for each one, with minimum and maximum values described as follows: AST -- cluster 1 (69 and 5,680 U/L) and 2 (6,260 and 12,970 U/L); ALT -- 1 (86 and 3,846 U/L) and 2 (4,160 and 8,064 U/L); urea -- 1 (15 and 93 mg/dL) and 2 (110 and 180 mg/dL); creatinine -- 1 (0.7 and 5.7 mg/dL) and 2 (7 and 17.5 mg/dL). The following cutoff points of serum laboratory results were significantly associated with higher chance of death: AST \> 6,000 U/L; ALT \> 4,000 U/L; urea \> 100 mg/dL; and creatinine \> 6 mg/dL. A subgroup of 20 cases of maximum AST values below 3,000 U/L had 5.0% lethality (one death), and another subgroup of 18 cases of ALT values below 3,500 U/L presented 5.6% lethality (one death). No association was observed between death and the variables of sex, age, race or skin color, education, year of disease reporting, delayed onset of symptoms and hospital admission, abdominal pain, and comorbidity.

Table 3Lethality and estimated chance of death according to some variables of confirmed cases of yellow fever admitted to HFSE/IEISS. Rio de Janeiro, RJ, Brazil, March 11, 2017 to June 15, 2018.Clinical variables and serum laboratory examsPresentAbsentChi-square test (p)Odds ratio95%CICasesDeathsCasesDeathsff%ff%Jaundice452146.7700.00.033^a^NANABleeding261765.426415.40.00010.3892.728--39.560Changes in renal excretion281967.92428.30.00023.2224.457--120.989Seizures6583.3461634.80.034^a^9.3751.007--87.284Leucopenia341029.4181161.10.0270.2650.079--0.881Max. AST^b^ \> 6,000 U/L201470.030516.70.00011.6673.009--45.239Max. ALT^c^ \> 4,000 U/L161381.335720.00.00017.3333.852--77.994Max. urea \> 100 mg/dL12975.0371129.70.0067.0911.607--31.296Max. creatinine \> 6 mg/dL12866.7401332.50.0344.1541.055--16.355HFSE/IEISS: *Hospital Federal dos Servidores do Estado* / *Instituto Estadual de Infectologia São Sebastião* ; NA: not evaluated.^a^ Fisher's exact test.^b^ Aspartate aminotransferase.^c^ Alanine aminotransferase.

Some logistic models were studied in the multivariate analysis, starting with a saturated model with sex, age, comorbidities, bleeding, changes in renal excretion, leukopenia and continuous laboratory variables (bilirubin, AST, ALT, urea, creatinine and platelet count), using the stepwise method. Model 1 ( [Table 4](#t4){ref-type="table"} ) kept a significant association with higher chance of death, changes in renal excretion, and increasing ALT values. Models 2 and 3 were built by the enter method, keeping the AST value, although it did not present statistical significance. These models kept the association of changes in renal excretion with higher chance of death. In addition, in model 2, where transaminases were categorized into ranges identified in the bivariate analysis (ALT ≤ 4,000 U/L and ALT \> 4,000 U/L; AST ≤ 6,000 U/L; AST \> 6,000 U/L), a significant association was found between higher chance of death and ALT \> 4,000 U/L, and borderline significance for AST \> 6,000 U/L. In model 3, transaminases vary every 1,000 U/L. At every increase of 1,000 U/L in ALT, a significant increase of 137% is observed in the chance of death, and an increase in borderline significance for AST. Models 1, 2, and 3 showed satisfactory agreements (85.7%, 88.0%, and 90.0%, respectively). The Hosmer-Lemeshow test confirmed satisfactory adjustments for all three models, obtaining non-significant values for the difference between expected and observed frequencies in each decile of estimated probability of death (p = 0.490, p = 0.179, and p = 0.799, respectively).

Table 4Multivariate analysis by logistic regression of factors associated with death in confirmed cases of yellow fever admitted to HFSE/IEISS. Rio de Janeiro, RJ, Brazil, March 11, 2017 to June 15, 2018.VariableParameterStandard errorpOdds ratio95%CIModel 1 (agreement: 85.7%)^a^     Intercept-6.5042.0630\--Changes in renal excretion (reference: absent)3.3141.290.0127.5012.193--344.82ALT (continuous)0.00100.0041.0011--1.002Model 2 (agreement: 88.0%)^b^     Intercept-4.481.4010.001\--Changes in renal excretion (reference: absent)3.4331.2610.00630.9772.618--366.563ALT \> 4,000 U/L (reference: ≤4,000 U/L)2.8111.1650.01616.6331.696--163.122AST \> 6,000 U/L (reference: ≤6,000 U/L)1.70.9260.0665.4710.891--33.582Model 3 (agreement: 90.0%)^c^     Intercept-8.1012.7730.003\--Changes in renal excretion (reference: absent)3.2181.4130.02324.9811.567--398.245ALT 1,000 (variation at every 1,000 U/L)0.8620.3990.0312.3671.083--5.177AST 1,000 (variation at every 1,000 U/L)0.3940.2260.0811.4830.953--2.310HFSE/IEISS: *Hospital Federal dos Servidores do Estado* and *Instituto Estadual de Infectologia São Sebastião*^a^ Model 1: stepwise forward, based on sex, age, comorbidity, changes in renal excretion, aspartate aminotransferase (AST), alanine aminotransferase (ALT), direct bilirubin, urea, creatinine, and leucopenia.^b^ Model 2: enter, with categorical ALT and AST.^c^ Model 3: enter, with ALT and AST on a scale of 1,000 units of variation.

Regarding the treatment, in addition to intensive support measures, high-volume plasma exchange was performed for removal of plasma cytokines and adhesion molecules and for coagulation factor replacement in 12 patients (23.1%), with 5 deaths (41.7%); lethality was 40.0% in remaining cases. Hemodialysis was performed in 21 cases (40.4%), with 16 deaths (lethality of 76.2% versus 16.1% in remaining cases; OR = 16.6; 95%CI 4.2--66.2). In a multivariate model controlling transaminases, urea, creatinine, and platelet count, the association between hemodialysis and death lost statistical significance (OR = 8.3; 95%CI 0.6--119.2).

DISCUSSION
==========

This study presented the profile of 52 confirmed cases of yellow fever whose patients were admitted to HFSE/IEISS, the hospital in charge of 17.9% of all cases in the State of Rio de Janeiro in 2017 and 2018. In 2017, SES/RJ confirmed 27 cases with 9 deaths^[@B13]^ ; in 2018, 264 cases and 85 deaths^[@B8]^ . The temporal distribution of hospitalized patients followed the dynamics of the outbreak in the state.

Male predominance is consistent with the literature^[@B14]^ . Median age (49.5 years) was higher than other studies: 26 and 27.5 years^[@B15]\ ,\ [@B16]^ . Case studies in the extra-Amazon region have reported median age closer to this study, such as median age of 36 years^[@B14]^ and mean age of 46.7 years^[@B18]^ . Differences in the distribution of cases of wild yellow fever by age and sex vary according to the degree of exposure to the woods^[@B14]^ .

The rural area of residence was observed in 61.5% of the cases, similar to another study^[@B14]^ . Regarding patient occupation, 40.4% were rural workers with exposure to the wild type of yellow fever; other studies report similar or higher percentages, from 41.7%^[@B17]^ to 79.2%^[@B14]\ ,\ [@B16]\ ,\ [@B18]^ . The contribution of tourism activity has been described^[@B14]\ ,\ [@B17]^ . A recent report showed 10 cases of yellow fever among travelers in Brazil, with four deaths; three were Chilean travelers, of these, two are included in this study^[@B21]^ .

Regarding vaccination status, in a study that analyzed 281 confirmed cases from 1999 to 2003, of which 37.4% were in the Amazon, 90.8% were unvaccinated and the remaining 9.2% received only one dose^[@B14]^ . In that study, individuals who received the vaccine up to ten days before the onset of symptoms were considered unvaccinated^[@B4]^ . Based on this criterion, only three cases of the present study would be considered effectively vaccinated. In the context of this study, excluding the differential diagnosis with adverse event after vaccination became relevant in cases of recent vaccination.

According to estimates, at least 90% of yellow fever cases are asymptomatic or oligosymptomatic, and 10% are severe forms associated with high lethality.^[@B5]^ Frequently reported symptoms are fever (85%^[@B18]^ to 94.4%^[@B15]\ ,\ [@B19]^ ), headache (70.3%^[@B18]^ to 83.3%^[@B15]\ ,\ [@B19]^ ), myalgia (27.8%^[@B19]^ to 76.5%^[@B18]^ ), and vomiting (69.4%^[@B19]^ to 75.8%^[@B15]^ ), in percentages that are similar to those found in this study -- except for headache, which was lower (53.8%).

However, the percentage found in this study for jaundice (86.5%) is higher than in other investigations of 35.5% to 69.1%^[@B15]\ ,\ [@B18]\ ,\ [@B19]^ . Also, changes in renal excretion (53.8%) are higher than reported by other authors: 16.7%^[@B19]^ to 36.7%^[@B15]^ . The latter reported bleeding at 46.4%, a percentage close to this study (50%).

According to the literature, around 15% of cases develop a visceral disease with jaundice. In this situation, the lethality rates range from 20% to 50%^[@B4]\ ,\ [@B22]^ . The lethality rate observed in Africa has been around 20%, generally lower than in South America (40%--60%)^[@B4]^ . The lethality rates reported in patients with severe viscerotropic or post-vaccination disease are high, above 50%, even in developed intensive care centers^[@B22]^ .

In Brazil, the lethality rate of severe cases varies between 40 and 60%^[@B5]\ ,\ [@B14]^ . Some studies report lower lethality rates, but with different severity profile. An outbreak in the State of Maranhão, with asymptomatic cases accounting for 40.0%, reported lethality rate of 17.5%^[@B20]^ . A recent study conducted in Minas Gerais found a lethality rate of 13.5%, but the frequency of jaundice was 35.5%^[@B18]^ , lower than this study (86.5%). An outbreak in MG, when 69.4% of patients were hospitalized, reported a lethality rate of 33.3%; in 19 cases classified as severe (with bleeding, liver and kidney failure, severe prostration, or coma), the lethality rate was 83.3%^[@B19]^ .

Based on the jaundice criterion only, 86.5% of the cases in this study would be of moderate or severe clinical form^[@B1]\ ,\ [@B4]^ . Another study described 70% of moderate to severe cases, 69.1% jaundice, and 44.2% deaths^[@B15]^ .

No association was observed between death and sex, age, race or skin color, education, year of disease reporting, period between symptom onset and hospital admission, abdominal pain, and comorbidity. A study confirmed cases in Brazil from 2000 to 2012^[@B16]^ found higher lethality rates among male patients (49.6%) than among female patients (39.7%), but the difference was not significant. A study analyzing cases from a previous period (1999--2002) found a significant association between higher chance of death and male patients and age over 40 years, but in the multivariate analysis, sex and age lost significance^[@B15]^ .

The median interval between symptom onset and admission to HFSE/IESS (five days) was slightly longer than another study (three days)^[@B19]^ . Both studies found no difference between this interval and death, which is in agreement with at least another study^[@B18]^ . In this study, the patients went first to other units, with subsequent referral to HFSE/IEISS.

A study conducted in MG^[@B18]^ reported a shorter hospitalization period than this study, and no difference regarding the outcome (mean = 5.70 days and SD = 3.78 days in the case of death; mean = 5.02 days and SD = 5.88 days for the survivors). Another study reported median hospitalization period until death of eight days^[@B19]^ , shorter than this study. The severity of the cases analyzed in this study and the use of intensive care, hemodialysis and high-volume plasma exchange are some factors possibly related to longer hospitalization period and high cost of care.

In general, the serum values of transaminases, bilirubin, urea and creatinine in this study were higher than those reported in the literature. A study analyzing 36 cases, 91.7% of severe and moderate forms^[@B19]^ , described for AST 47 to 7,500 U/L (mean = 1,027.8); ALT 26 to 6,600 U/L (mean = 815.8); DB 0.2 to 12.4 mg/dL (mean = 3.2); urea 10 to 175 mg/dL (mean = 56.5); creatinine 0.6 to 13 mg/dL (mean = 2.9). Another study^[@B15]^ analyzing 251 cases, 70.4% of moderate to severe forms, reported lower median values of transaminases, although the maximum values were higher than those found in this study: AST median 1,096 U/L (ranging from 13 to 43,460); ALT median 957 U/L (9 to 15,250); DB median 4.7 mg/dL (0.4 to 77.0). However, for urea and creatinine, their values were higher: urea median 106 mg/dL (11 to 328), and creatinine median 3.6 mg/dL (1.0 to 19.0).

In this and in the two other studies^[@B15]\ ,\ [@B19]^ , AST increases generally exceeded those of ALT, which is described in the literature^[@B5]\ ,\ [@B23]^ probably due to the cytopathic effect of the virus on the myocardium and skeletal muscles; ALT is more specific for liver disease than AST. Regarding the increased bilirubin level, it was mainly due to the increase in direct-reacting fraction, in agreement with the literature^[@B5]^ .

In this study, a significant association was found between higher AST, ALT, DB, urea and creatinine values and death, and between lower platelet count and death values. In the multivariate analysis, only changes in renal excretion and ALT remained significantly associated with higher chance of death; AST maintained an association with threshold p value. Another study^[@B15]^ found an association with higher chance of death for male patients, age \> 40 years, jaundice, AST \> 1,200 U/L, ALT \> 1,500 U/L, TB \> 7 mg/dL, DB \> 5 mg/dL, and urea \> 100 mg/dL. However, the multivariate analysis showed associations only with jaundice and AST \> 1,200 U/L.

No specific treatment has been defined so far. Hospitalization of severe forms is recommended in hospitals that offer intensive care and dialysis^[@B1]\ ,\ [@B2]\ ,\ [@B23]^ . Some antiviral drugs have been evaluated, such as ribavirin, thiazofurine, carboxamide, and pyrazoline compounds^[@B4]\ ,\ [@B22]^ , and more recently, sofosbuvir^[@B7]^ . Catastrophic terminal events associated with severe cases, possibly related to a systemic inflammatory response syndrome, represent a potential field for evaluating the role of interventions such as high-volume plasma exchange^[@B7]^ , which was performed at the institution. It was based on the logic of fulminant hepatitis management guidelines; the protocol used was that reported by Larsen et al.^[@B24]^ , adapted to the circumstances of yellow fever outbreak.

Liver transplantation in fulminant hepatitis attributed to yellow fever was first performed in December 2017 in São Paulo, and its role was not well clarified^[@B7]\ ,\ [@B23]\ ,\ [@B25]^ . In this study, one case was transferred to another unit for liver transplantation, progressing to death less than 24 hours after the transfer during the transplant surgery (death included in this study).

Reemergence of yellow fever outside the Amazon region reached regions near large urban centers, and a large part of local population was not vaccinated. In the last two years, the disease has disseminated, particularly in the Southeast region, resulting in the largest epidemic in recent decades. The causes of this expansion have not been clearly explained; environmental factors and alterations of the virus itself have been investigated^[@B7]^ . In 2017, a mutation in viral replication enzymes was identified, but its impact has not been fully explained^[@B26]^ . A recent study reported the yellow fever virus responsible for outbreaks from 2016 to 2018 in the Southeast region in Brazil belongs to a monophyletic lineage (BR-YFV_2016/18), probably coming from the Midwest to the Southeast. Its persistence in the Southeast suggests that this region has proper ecological and climatic conditions for virus survival during epidemic and interepidemic periods^[@B27]^ . Described factors include extended rainy season associated with abundant vectors, deforestation for agriculture, epizootic transmission, and displacement of individuals in virus period^[@B4]\ ,\ [@B28]^ .

High infestation of *Aedes aegypti* in several urban centers of these regions, increased number of wild yellow fever cases, and low vaccination coverage are factors that favor the risk of disease reurbanization. Recent outbreaks of wild yellow fever starting in December 2016 in the states of MG, ES, RJ and SP, and confirmed deaths of monkeys in other states have once again emphasized the relevance of adopting measures to reduce the risk of reurbanization, with changes in vaccination recommendations, including expansion of recommended vaccination areas and fractional dose campaigns^[@B3]\ ,\ [@B7]^ .

In this context, this study presented the experience of a hospital that significantly contributed to the treatment of severe cases of yellow fever in the state. The severity of the cases is represented by the high percentage of jaundice (86.5%), changes in renal excretion (53.8%), and bleeding (50.0%), besides the higher median values of serum transaminases. Providing care to these patients involves a highly complex structure adapted to respond to emergencies and representing a great challenge for the health team. A deeper knowledge about the profile of these cases, especially the factors associated with higher chance of death, may contribute to discussions regarding the role of therapeutic interventions such as high-volume plasma exchange. Study limitations are mainly related to the quality of information from the epidemiological surveillance system, which was minimized after the review, and data complementation with medical records during the epidemiological investigation and case end process, which is part of the epidemiology service routine^[@B9]^ . Missing information was less than 5% for most of the analyzed variables, except for education (15.0%) and maximum urea (7.7%), and much lower when compared to other studies^[@B15]^ .

Active epidemiological surveillance contributed to fast reporting to health authorities, monitoring of sample collection to confirm the cases, and the maintenance of an information system that, even during an outbreak, was able to support this study. The study contributed to a better understanding of the profile of yellow fever cases in HFSE/IEISS, which admitted 17.9% of the confirmed cases in RJ in this period, showing a high severity profile. The main predictors of death were changes in renal excretion and elevated serum transaminases, especially ALT. High lethality emphasizes the need for early diagnosis and treatment, and the importance of increasing vaccination coverage.

Artigo Original

Febre amarela: perfil dos casos e fatores associados ao óbito em hospital referência no estado do Rio de Janeiro, 2017--2018

https://orcid.org/0000-0003-0273-6911

Escosteguy

Claudia Caminha

I

https://orcid.org/0000-0001-9919-4455

Pereira

Alessandra Gonçalves Lisbôa

I

II

https://orcid.org/0000-0002-0809-3673

Marques

Marcio Renan Vinícius Espínola

I

https://orcid.org/0000-0002-8043-2350

Lima

Tatiana Rodrigues de Araujo

I

III

https://orcid.org/0000-0003-0348-8374

Galliez

Rafael Mello

IV

V

https://orcid.org/0000-0003-4073-3930

Medronho

Roberto de Andrade

V

VI

Hospital Federal dos Servidores do Estado. Serviço de Epidemiologia. Rio de Janeiro, RJ, Brasil

Universidade Estácio de Sá. Faculdade de Medicina. Rio de Janeiro, RJ, Brasil

Universidade do Estado do Rio de Janeiro. Faculdade de Enfermagem. Rio de Janeiro, RJ, Brasil

Instituto Estadual de Infectologia São Sebastião. Rio de Janeiro, RJ, Brasil

Universidade Federal do Rio de Janeiro. Faculdade de Medicina. Rio de Janeiro, RJ, Brasil

Universidade Federal do Rio de Janeiro. Instituto de Estudos em Saúde Coletiva. Rio de Janeiro, RJ, Brasil

Correspondência: Claudia Caminha Escosteguy Serviço de Epidemiologia Hospital Federal dos Servidores do Estado Rua Sacadura Cabral 178 20221-903 Rio de Janeiro, RJ, Brasil. E-mail: cescosteguy\@hse.rj.saude.gov.br

Contribuição dos Autores: Concepção e planejamento do estudo: CCE. Coleta, análise e interpretação de dados: CCE, AGLP, MRVEM, TRAL, RMG, RAM. Elaboração ou revisão do artigo: CCE, AGLP, MRVEM, TRAL, RMG, RAM. Aprovação da versão final: CCE, AGLP, MRVEM, TRAL, RMG, RAM. Responsabilidade pública pelo conteúdo do artigo: CCE, AGLP, MRVEM, TRAL, RMG, RAM.

Conflito de Interesses: Os autores declaram não haver conflito de interesses.

OBJETIVO
========

Descrever o perfil clínico-epidemiológico dos casos confirmados de febre amarela internados em hospital geral de referência para doenças infecciosas no estado do Rio de Janeiro, Brasil, de 11 de março de 2017 a 15 de junho de 2018, durante recente surto e fatores associados ao óbito.

MÉTODOS
=======

Estudo observacional retrospectivo, com análise de bases de dados secundários da vigilância epidemiológica local e coleta complementar de dados nas fichas de investigação epidemiológica e prontuários clínicos. As variáveis analisadas incluíram dados demográficos, epidemiológicos, clínicos e laboratoriais. Foi conduzida análise estatística descritiva bivariada e múltipla por regressão logística para estudo de fatores associados ao óbito.

RESULTADOS
==========

Foram internados 52 casos confirmados, 86,5% deles homens, com mediana de idade de 49,5 anos e 40,4% trabalhadores rurais. Os sinais e sintomas mais frequentes foram: febre (90,4%), icterícia (86,5%), náuseas e/ou vômitos (69,2%), alterações de excreção renal (53,8%), hemorragias (50%) e dor abdominal (48,1%), com comorbidade em 38,5% dos casos. A letalidade foi de 40,4%. Os fatores associados significativamente à maior chance de óbito na análise bivariada foram: hemorragia, alterações de excreção renal e valores máximos de bilirrubina direta, aspartato aminotransferase (AST), alanina aminotransferase (ALT), ureia e creatinina. Na análise múltipla por regressão logística, apenas alterações de excreção renal e ALT permaneceram como preditores significativos de maior chance de óbito. Observou-se ainda efeito limítrofe para AST. Os pontos de corte identificados como de alto risco para óbito foram ALT \> 4.000 U/L e AST \> 6.000 U/L.

CONCLUSÕES
==========

O estudo contribuiu para o conhecimento do perfil de casos confirmados de febre amarela com gravidade alta. Os principais fatores associados ao óbito foram a alteração da excreção renal e a elevação sérica de transaminases, sobretudo a ALT. A letalidade elevada reforça a necessidade de diagnóstico e tratamento precoces, e a importância do incremento da cobertura vacinal.

Febre Amarela, epidemiologia

Mortalidade Hospitalar

Fatores de Risco

Epidemiologia Descritiva

INTRODUÇÃO
==========

A febre amarela é uma arbovirose produzida por um *Flavivirus* , família *Flaviviridae.* No ciclo de transmissão urbana, o *Aedes aegypti* é seu principal vetor. No ciclo silvestre, é uma zoonose transmitida no continente americano pelos vetores *Haemagogus* e *Sabethes* ^[@B1]^. A forma grave caracteriza-se por lesão hepática importante, apresentando manifestações de insuficiência hepática e renal que podem levar ao óbito. A vacinação é a medida preventiva mais importante^[@B3]^.

A doença é endêmica e enzoótica em diversas regiões tropicais das Américas e da África, com a ocorrência de surtos periódicos. No Brasil, eram descritos casos de forma endêmica, principalmente na região amazônica, com surtos esporádicos fora dessa área^[@B3]^.

Em dezembro de 2016, o vírus reemergiu no sudeste brasileiro, iniciando o que até então foi o maior surto de febre amarela silvestre das últimas décadas no país, com 779 casos humanos confirmados no período de monitoramento de julho de 2016 a junho de 2017 e 262 óbitos (letalidade de 33,6%). Os quatro estados da região Sudeste apresentaram o maior número de casos: Minas Gerais (MG), Espírito Santo (ES), São Paulo (SP) e Rio de Janeiro (RJ). Essa região possui grandes centros urbanos, com população que, em grande parte, não estava imunizada contra a doença e muitas localidades com alta densidade de infestação pelo *Aedes aegypti* ^[@B3]\ ,\ [@B4]^.

No período de julho de 2017 a 16 de maio de 2018, ocorreu novo surto de maior magnitude no país, com 1.266 casos humanos confirmados e 415 óbitos (letalidade de 32,8%), predominando MG, SP e RJ^[@B6]^. Foram também confirmados óbitos em primatas não humanos em outros estados brasileiros, levantando a relevância da adoção de medidas para reduzir o risco de reurbanização da doença, com ampliação das áreas de vacinação recomendada e início das campanhas com aplicação da dose fracionada^[@B3]\ ,\ [@B7]^.

Em 2018, segundo dados da Secretaria de Estado de Saúde do Rio de Janeiro (SES/RJ) atualizados em 5 de julho de 2018, havia neste estado 264 casos confirmados, em 32 municípios, com 85 óbitos (32,2%); 13 localidades tinham epizootias confirmadas, com morte de macacos^[@B8]^.

Historicamente, no RJ, o Instituto Estadual de Infectologia São Sebastião (IEISS), uma referência para atendimento de doenças infecciosas, foi integrado à área física do Hospital Federal dos Servidores do Estado (HFSE) em 20 de agosto de 2012. O HFSE, por sua vez, é um hospital geral, federal e de ensino, que integra a Rede de Vigilância Epidemiológica Hospitalar de Interesse Nacional^[@B9]^. Nesse contexto do surto de febre amarela, essa estrutura aqui denominada HFSE/IEISS teve importante papel na atenção aos casos graves, internando 52 pacientes confirmados de 11 de março de 2017 a 15 de junho de 2018. O objetivo deste estudo é descrever o perfil clínico-epidemiológico desses casos e os fatores associados ao óbito.

MÉTODOS
=======

Realizou-se este estudo em um hospital referência para doenças infecciosas do RJ que conta com um serviço de epidemiologia integrante da rede nacional, o qual realiza busca ativa dos casos atendidos na unidade^[@B9]^. O RJ tem como limites os estados de MG, ES e SP, além do Oceano Atlântico. Ocupa 43.781,588 km^2^distribuídos em 92 municípios, com 16.718.956 habitantes em 2017, sendo 96,7% em área urbana^[@B10]^. Cerca de 30% da área do estado é ocupada por Mata Atlântica^[@B11]^.

De 11 de março de 2017 a 15 de junho de 2018, foram notificados no HFSE/IEISS 68 casos suspeitos da doença, de acordo com a definição para fins de vigilância epidemiológica: "indivíduo com quadro febril agudo (até sete dias), de início súbito, acompanhado de icterícia ou manifestações hemorrágicas, residente em (ou procedente de) área de risco para febre amarela ou de locais com ocorrência de epizootia confirmada em primatas não humanos ou isolamento de vírus em mosquitos vetores, nos últimos 15 dias, não vacinado contra febre amarela ou com estado vacinal ignorado"^[@B1]\ ,\ [@B2]^. Desses, 52 foram confirmados e internados no hospital (43 em 2018), constituindo a amostra do estudo. O critério de confirmação foi o exame de reação em cadeia da polimerase (PCR) detectável em 51 casos, enquanto o outro foi confirmado por vínculo epidemiológico^[@B1]\ ,\ [@B2]^.

O delineamento foi observacional, retrospectivo, com análise de bases de dados secundários da vigilância epidemiológica no HFSE a partir do Sistema de Informação de Agravos de Notificação (Sinan) e coleta complementar de dados dos prontuários clínicos, realizada pela equipe do serviço de epidemiologia, durante o processo de investigação epidemiológica dos casos. Analisaram-se variáveis demográficas, epidemiológicas, clínicas e laboratoriais em banco de dados construído em planilha eletrônica, exportado a partir do Sinan e complementado pela digitação de variáveis adicionais às existentes na ficha de investigação de febre amarela^[@B2]\ ,\ [@B12]^, correspondentes a sinais, sintomas e exames laboratoriais (detalhadas nas [Tabela 1](#t1002){ref-type="table"} e [Tabela 2](#t2002){ref-type="table"}).

Tabela 1Perfil dos 52 casos confirmados de febre amarela internados no HFSE/IEISS. Rio de Janeiro, RJ, Brasil, 11 de março de 2017 a 15 de junho de 2018.Dados clínicosf%Sexo masculino4586,5Faixa etária (anos)  13--341223,135--491426,950--591325,060--751325,0Febre4790,4Icterícia4586,5Náuseas/vômitos3669,2Cefaleia2853,8Alteração de excreção renal (oligúria, anúria ou ambas)2853,8Hemorragia2650,0Dor abdominal2548,1Mialgia1732,7Prostração/astenia1426,9Diarreia917,3Colúria917,3Artralgia611,5Convulsões611,5Dor retro-orbitária23,8Edema articular23,8Exantema11,9Sinal de Faget11,9Hiperemia conjuntival11,9Plaquetopenia \< 100.000/mm^3^4586,5Leucopenia3465,4Comorbidade (pelo menos uma)2038,5Hipertensão arterial1019,2Etilismo917,3Diabetes59,6Tabagismo47,7Esteatose hepática23,8Artrite reumatoide23,8Antecedentes epidemiológicos e conclusão da investigação  Presença de *Aedes aegypti* na região5198,1Epizootias no município de residência do caso3567,3Vacinado contra febre amarela917,3Classificação final como febre amarela silvestre52100,0Critério de confirmação laboratorial (PCR)5198,1Caso autóctone do município de residência3465,4Doença ocupacional1019,2Evolução  Óbito por febre amarela silvestre2140,4Cura3159,6HFSE/IEISS: Hospital Federal dos Servidores do Estado e Instituto Estadual de Infectologia São Sebastião; PCR: reação em cadeia da polimerase

Tabela 2Distribuição dos valores séricos de alguns exames segundo a evolução dos casos confirmados de febre amarela internados no HFSE/IEISS. Rio de Janeiro, RJ, Brasil, 11 de março de 2017 a 15 de junho de 2018.Valores séricosTotal de casosÓbitoNão óbitoTeste de Mann-Whitney (p)nMediana (mínimo--máximo)nMediana (mínimo--máximo)nMediana (mínimo--máximo)AST máxima (U/L)504.833 (69--12.970)198.460 (1.803--12.970)311.820 (69--10.900)0,000ALT máxima (U/L)512.920 (86--8.064)205.379 (1.943--8.064)311.581(86--5.428)0,000BT máxima (mg/dL)525,62 (0,70--38,00)217,00 (2,00--38,00)314,23 (0,70--29,00)0,063BD máxima (mg/dL)514,03 (0,09--20,00)215,00 (2,00--20,00)303,07 (0,09--17,00)0,043Ureia máxima (mg/dL)4954 (15--180)2093 (45--161)2936 (15--180)0,000Creatinina máxima (mg/dL)521,72 (0,7--17,5)213,2 (0,80--11,7)311,2 (0,7--17,5)0,000Plaquetemia mínima (por mm^3^)5250.000 (10.000--232.000)2138.000 (10.000--26.000)3168.000 (15.000--232.000)0,008Hematócrito mínimo (%)5036,0 (12,9--51,6)2029,5 (13,2--51,6)3038,5 (12,9--50,0)0,081HFSE/IEISS: Hospital Federal dos Servidores do Estado e Instituto Estadual de Infectologia São Sebastião; AST: aspartato aminotransferase; ALT: alanina aminotransferase; BT: bilirrubina total; BD: bilirrubina direta.

A análise estatística foi realizada no programa SPSS v.18, envolvendo análise descritiva bivariada e múltipla por regressão logística para estudo da associação das variáveis independentes com o desfecho óbito. Para estimar a chance de óbito, foram usadas *odds ratio* (OR) e seus respectivos intervalos de confiança de 95% (IC95%).

Na análise bivariada, utilizou-se o teste qui-quadrado de Pearson ou o teste exato de Fisher para as variáveis categóricas, e o teste de Mann-Whitney para as variáveis contínuas. Considerou-se estatisticamente significativo o valor de p \< 0,05. Para identificar o ponto de corte para variáveis numéricas correspondentes aos resultados de exames laboratoriais, utilizou-se a análise de agrupamentos por *K-means* , que consiste na subdivisão de um conjunto de dados em um número previamente escolhido de agrupamentos. Esse tipo de análise é utilizado quando não temos hipótese *a priori* sobre a estrutura ou comportamento dos dados e constitui um agrupamento não hierárquico por repartição. Optou-se por subdividir os dados de cada variável contínua em dois agrupamentos, utilizando como ponto de partida a identificação dos valores mínimos e máximos registrados. Ao final do processo, obteve-se um ponto de corte aproximado entre a média do valor máximo do primeiro agrupamento e o mínimo do agrupamento seguinte.

Para a regressão logística, foram incluídas as variáveis que apresentaram associação com o óbito na análise bivariada prévia, com p \< 0,10, e aquelas consideradas de importância clínica (como idade, sexo, comorbidade e dor abdominal) ou de interesse (como ano de notificação). O teste de Wald foi usado para testar a significância das variáveis independentes incluídas nos modelos estudados. Para a análise do ajuste global, utilizou-se o teste da razão de verossimilhança ( *-2 log likelihood* ). Foi analisada a concordância entre as probabilidades preditas pelos modelos e as respostas observadas, e usado o teste de Hosmer-Lemeshow.

Estudo incluído em projeto aprovado pelo Comitê de Ética em Pesquisa do HFSE (parecer CEP-HFSE 000.534 de 14 de julho de 2014).

RESULTADOS
==========

A [Figura 1](#f01002){ref-type="fig"} apresenta a distribuição temporal dos casos por semana epidemiológica da notificação; 35 (78,8%) ocorreram de janeiro a março de 2018. Desses, 45 (86,5%) eram homens e sete (13,5%) mulheres, com idade entre 13 e 75 anos (mediana de 49,5 anos). A raça ou cor de pele autorreferida foi branca em 29 (55,8%), parda em 15 (28,8%), preta em sete (13,5%), e amarela em um caso (1,9%); 27 casos tinham no máximo ensino fundamental incompleto (73,0%; excluídos 15 com escolaridade ignorada).

Figura 1Distribuição segundo semana epidemiológica da notificação dos casos confirmados de febre amarela internados no Hospital Federal dos Servidores do Estado/Instituto Estadual de Infectologia São Sebastião. Rio de Janeiro, RJ, Brasil, 11 de março de 2017 a 15 de junho de 2018.

Houve casos de 18 municípios do RJ, sendo 50 residentes e dois turistas chilenos. Em 2018, 21 casos foram oriundos da região turística da Costa Verde, sendo 18 da Baía de Ilha Grande (16 residentes e os dois turistas chilenos). A zona de residência ou estadia era rural em 32 (61,5%), urbana em 11 (21,2%), periurbana em dois (3,8%) e ignorada em sete (13,5%). A ocupação predominante era trabalhador rural (21 casos; 40,4%); três casos realizavam atividades turísticas (dois turistas e um guia).

A [Tabela 1](#t1002){ref-type="table"} apresenta o perfil dos casos segundo variáveis clínicas, epidemiológicas e conclusão da investigação epidemiológica. Os sinais e sintomas mais frequentes foram: febre (90,4%), icterícia (86,5%) e náuseas e vômitos (69,2%). Alterações de excreção renal (oligúria ou anúria) ocorreram em 53,8%, hemorragias em 50,0% e dor abdominal em 48,1%. Plaquetopenia \< 100.000/mm^3^ocorreu em 86,5% e leucopenia em 65,4%.

Em 38,5% dos casos, descreveu-se pelo menos uma comorbidade, predominando a hipertensão arterial sistêmica (19,2% dos casos), etilismo (17,3%) e diabetes (9,6%). Em 98,1% relatou-se presença de *Aedes aegypti* em área urbana por onde o paciente circulou. Epizootias em primatas não humanos foram relatadas no município de residência de 67,3%.

Em nove casos (17,5%), havia história de vacinação prévia contra febre amarela; o intervalo entre a data da vacina e o início dos sintomas foi de até quatro dias em cinco deles; entre 11 e 12 dias em dois; sete anos em um; e um caso foi vacinado no terceiro dia do início dos sintomas. Nos casos com história de vacinação prévia recente, houve comprovação do vírus selvagem por sequenciamento, afastando-se evento adverso pós-vacinação.

Em 65,4% dos casos, a transmissão foi autóctone do município de residência; nos demais, indeterminada, por haver deslocamento para outros municípios do próprio RJ. Em 19,2%, o vínculo ocupacional foi bem caracterizado ( [Tabela 1](#t1002){ref-type="table"} ). Quanto à evolução, 21 casos (40,4%) foram a óbito (19 em 2018 e 2 em 2017).

O retardo entre o início dos sintomas e a admissão no HFSE/IEISS variou de um a 15 dias, com mediana de cinco, semelhante entre os casos que faleceram e os que não faleceram. O tempo entre início dos sintomas e o óbito variou de quatro a 22 dias, com mediana de nove. O tempo de permanência no hospital variou de um a 56 dias, com mediana de 10, sem diferença significativa entre óbitos (1 a 26 dias; mediana = 11) e sobreviventes (3 a 56 dias; mediana = 10). O intervalo entre a admissão e a notificação do caso à vigilância epidemiológica variou entre zero e três dias, com mediana de um; 86,5% foram notificados em até 24 horas da admissão.

A [Tabela 2](#t2002){ref-type="table"} apresenta a distribuição dos valores séricos máximos de aspartato aminotransferase (AST), alanina aminotransferase (ALT), bilirrubina total (BT), bilirrubina direta (BD), ureia, creatinina e o menor valor de plaquetemia e de hematócrito para o conjunto dos casos e segundo o desfecho óbito. Houve associação significativa entre maiores valores de AST, ALT, BD, ureia e creatinina e óbito, assim como entre menores valores de plaquetemia e óbito.

Segundo a [Tabela 3](#t3002){ref-type="table"} , a presença dos seguintes sinais e sintomas esteve significativamente associada à maior chance de óbito: icterícia, hemorragia, alterações de excreção renal e convulsões. O relato de leucopenia associou-se significativamente a uma menor letalidade. Na [Tabela 3](#t3002){ref-type="table"} , os pontos de corte para AST, ALT, ureia e creatinina foram identificados pela análise por *K-means* , que definiu, para cada uma, dois clusters (1 e 2), com seus valores mínimos e máximos descritos a seguir: AST -- cluster 1 (69 e 5.680 U/L) e 2 (6.260 e 12.970 U/L); ALT -- 1 (86 e 3.846 U/L) e 2 (4.160 e 8.064 U/L); ureia -- 1 (15 e 93 mg/dL) e 2 (110 e 180 mg/dL); creatinina -- 1 (0,7 e 5,7 mg/dL) e 2 (7 e 17,5 mg/dL). Os seguintes pontos de corte de resultados laboratoriais séricos se associaram significativamente à maior chance de óbito: AST \> 6.000 U/L; ALT \> 4.000 U/L, ureia \> 100 mg/dL e creatinina \> 6 mg/dL. Um subgrupo de 20 casos com valores máximos de AST abaixo de 3.000 U/L teve letalidade de 5,0% (um óbito), e outro de 18 casos com ALT abaixo de 3.500 U/L apresentou letalidade de 5,6% (um óbito). Não foi observada associação entre o óbito e as variáveis sexo, faixa etária, raça ou cor de pele, escolaridade, ano de notificação, retardo entre início dos sintomas e internação no hospital, dor abdominal e comorbidade.

Tabela 3Letalidade e estimativa da chance de óbito segundo algumas variáveis dos casos confirmados de febre amarela internados no HFSE/IEISS. Rio de Janeiro, RJ, Brasil, 11 de março de 2017 a 15 de junho de 2018.Variáveis clínicas e exames laboratoriais séricosPresenteAusenteTeste qui-quadrado (p)*Odds ratio*IC95%CasosÓbitosCasosÓbitosff%ff%Icterícia452146,7700,00,033^a^NANAHemorragia261765,426415,40,00010,3892,728--39,560Alteração da excreção renal281967,92428,30,00023,2224,457--120,989Convulsões6583,3461634,80,034^a^9,3751,007--87,284Leucopenia341029,4181161,10,0270,2650,079--0,881AST^b^máxima \> 6.000 U/L201470,030516,70,00011,6673,009--45,239ALT^c^máxima \> 4.000 U/L161381,335720,00,00017,3333,852--77,994Ureia máxima \> 100 mg/dL12975,0371129,70,0067,0911,607--31,296Creatinina máxima \> 6 mg/dL12866,7401332,50,0344,1541,055--16,355HFSE/IEISS: Hospital Federal dos Servidores do Estado e Instituto Estadual de Infectologia São Sebastião; NA: não avaliado^a^Teste exato de Fisher^b^Aspartato aminotransferase^c^Alanina aminotransferase

Na análise múltipla, alguns modelos logísticos foram estudados. Partiu-se de um modelo saturado com sexo, idade, comorbidades, hemorragia, alteração de excreção renal, leucopenia e variáveis laboratoriais contínuas (bilirrubinas, AST, ALT, ureia, creatinina e plaquetemia), pelo método *stepwise* . Permaneceram no modelo 1 ( [Tabela 4](#t4002){ref-type="table"} ), com associação significativa com maior chance de óbito, a presença de alteração de excreção renal e valores crescentes de ALT. Os modelos 2 e 3 foram construídos pelo método *enter* , optando-se por manter a AST, apesar de ela não ter alcançado significância estatística. Neles, a associação da alteração de excreção renal com maior chance de óbito permaneceu. Adicionalmente, no modelo 2, no qual as transaminases foram categorizadas em faixas identificadas na análise bivariada (ALT ≤ 4.000 U/L e ALT \> 4.000 U/L; AST ≤ 6.000 U/L e AST \> 6.000 U/L), observou-se associação significativa entre maior chance de óbito e ALT \> 4.000 U/L, e significância limítrofe para AST \> 6.000 U/L. No modelo 3, as transaminases estão em escala que varia a cada 1.000 U/L. A cada aumento de 1.000 U/L no valor da ALT, há um aumento significativo de 137% na chance de óbito, e um aumento de significância limítrofe no caso da AST. Os modelos 1, 2 e 3 apresentaram concordâncias satisfatórias (85,7%, 88,0% e 90,0% respectivamente). O teste de Hosmer-Lemeshow confirmou ajuste satisfatório para os três, obtendo valores não significativos para a diferença entre as frequências observadas e esperadas dentro de cada decil de probabilidade estimada de óbito (p = 0,490, p = 0,179 e p = 0,799, respectivamente).

Tabela 4Análise múltipla por regressão logística dos fatores associados ao óbito nos casos confirmados de febre amarela internados no HFSE/IEISS. Rio de Janeiro, RJ, Brasil, 11 de março de 2017 a 15 de junho de 2018.VariávelParâmetroErro-padrãop*Odds ratio*IC95%Modelo 1 (concordância: 85,7%)^a^     Intercepto-6,5042,0630\--Alteração de excreção renal (referência: ausente)3,3141,290,0127,5012,193--344,82ALT (contínua)0,00100,0041,0011--1,002Modelo 2 (concordância: 88,0%)^b^     Intercepto-4,481,4010,001\--Alteração de excreção renal (referência: ausente)3,4331,2610,00630,9772,618--366,563ALT \> 4.000 U/L (referência: ≤ 4.000 U/L)2,8111,1650,01616,6331,696--163,122AST \> 6.000 U/L (referência: ≤ 6.000 U/L)1,70,9260,0665,4710,891--33,582Modelo 3 (concordância: 90,0%)^c^     Intercepto-8,1012,7730,003\--Alteração de excreção renal (referência: ausente)3,2181,4130,02324,9811,567--398,245ALT 1.000 (variação a cada 1.000 U/L)0,8620,3990,0312,3671,083--5,177AST 1.000 (variação a cada 1.000 U/L)0,3940,2260,0811,4830,953--2,310HFSE/IEISS: Hospital Federal dos Servidores do Estado e Instituto Estadual de Infectologia São Sebastião^a^Modelo 1: *stepwise forward* a partir de sexo, idade, comorbidade, alteração da excreção renal, aspartato aminotransferase (AST), alanina aminotransferase (ALT), bilirrubina direta, ureia, creatinina e leucopenia.^b^Modelo 2: *enter* com ALT e AST categóricas.^c^Modelo 3: *enter* com ALT e AST em escala de 1.000 unidades de variação.

Quanto ao tratamento, além das medidas de suporte intensivo, a troca plasmática de alto volume com objetivo de remoção de citocinas plasmáticas e moléculas de adesão e reposição de fatores de coagulação foi realizada em 12 pacientes (23,1%), ocorrendo 5 óbitos (41,7%); a letalidade nos demais casos foi de 40,0%. Hemodiálise foi realizada em 21 casos (40,4%), com 16 óbitos (letalidade de 76,2% *versus* 16,1% nos demais; OR = 16,6; IC95% 4,2--66,2). Em modelo multivariado controlando transaminases, ureia, creatinina e plaquetemia, a associação entre hemodiálise e óbito perdeu a significância estatística (OR = 8,3; IC95% 0,6--119,2).

DISCUSSÃO
=========

Este estudo apresentou o perfil de 52 casos confirmados de febre amarela internados no HFSE/IEISS, que foi responsável pela hospitalização de 17,9% dos casos confirmados no estado do Rio de Janeiro em 2017 e 2018. Em 2017, a SES/RJ confirmou 27 casos com 9 óbitos^[@B13]^; em 2018, 264 casos e 85 óbitos^[@B8]^. A distribuição temporal dos casos internados no hospital acompanhou a dinâmica do surto no estado.

O predomínio do sexo masculino é coerente com a literatura^[@B14]^. A mediana de idade (49,5 anos) foi maior do que a de outros estudos: 26 e 27,5 anos^[@B15]\ ,\ [@B16]^. Estudos de casos na região extra-amazônica têm relatado distribuições etárias mais próximas à deste estudo, como mediana de 36 anos^[@B14]^e média de 46,7 anos^[@B18]^. As diferenças de distribuição dos casos de febre amarela silvestre por idade e sexo têm variado de acordo com o grau de exposição à mata^[@B14]^.

A zona de residência foi considerada rural em 61,5% dos casos, percentual próximo ao de outro estudo^[@B14]^. Quanto à ocupação, 40,4% eram trabalhadores rurais com evidente exposição ao ciclo silvestre; outros estudos relatam percentuais próximos ou maiores, de 41,7%^[@B17]^a 79,2%^[@B14]\ ,\ [@B16]\ ,\ [@B18]^. A contribuição da atividade turística tem sido descrita^[@B14]\ ,\ [@B17]^. Relato recente mostrou 10 casos de febre amarela em viajantes no Brasil, com quatro óbitos; três deles eram chilenos, dos quais dois estão incluídos no presente estudo^[@B21]^.

Com relação ao estado vacinal, estudo sobre 281 casos confirmados de 1999 a 2003, dos quais 37,4% eram da Amazônia, relatou que 90,8% eram não vacinados e que os 9,2% restantes receberam apenas uma dose^[@B14]^. Naquele estudo, o indivíduo que recebera a vacina até dez dias antes do início dos sintomas foi considerado não vacinado^[@B4]^. Por esse critério, apenas três casos do presente estudo seriam considerados efetivamente vacinados. No contexto deste estudo, tornou-se relevante a exclusão do diagnóstico diferencial com evento adverso pós-vacinação nos casos com história de vacinação recente.

Estima-se que pelo menos 90% dos casos de febre amarela sejam assintomáticos ou oligossintomáticos, e que 10% sejam formas graves associadas a letalidade alta.^[@B5]^Sintomas gerais comumente relatados são febre (85%^[@B18]^a 94,4%^[@B15]\ ,\ [@B19]^), cefaleia (70,3%^[@B18]^a 83,3%^[@B15]\ ,\ [@B19]^), mialgia (27,8%^[@B19]^a 76,5%^[@B18]^) e vômitos (69,4%^[@B19]^a 75,8%^[@B15]^), em percentuais próximos ao deste estudo -- à exceção de cefaleia, que foi menor (53,8%).

Entretanto, o percentual de 86,5% de icterícia deste estudo é maior do que o relatado por outros, que variam de 35,5% a 69,1%^[@B15]\ ,\ [@B18]\ ,\ [@B19]^. Também nosso percentual de alterações de excreção renal (53,8%) é maior do que relatado por outros autores: 16,7%^[@B19]^a 36,7%^[@B15]^. Esse último estudo^[@B15]^relatou 46,4% de manifestações hemorrágicas, percentual próximo ao nosso (50%).

Segundo a literatura, aproximadamente 15% dos casos desenvolvem doença visceral com icterícia. Nessa situação, as taxas de letalidade variam de 20% a 50%^[@B4]\ ,\ [@B22]^. A letalidade observada na África tem sido em torno de 20%, em geral menor do que na América do Sul (40%--60%)^[@B4]^. As letalidades relatadas em pacientes com doença viscerotrópica ou pós-vacinal grave são elevadas, acima de 50%, mesmo em centros desenvolvidos e com terapia intensiva^[@B22]^.

No Brasil, a letalidade dos casos graves oscila entre 40 e 60%^[@B5]\ ,\ [@B14]^. Há estudos com letalidades menores, porém com perfil de gravidade diferente. Um surto no estado do Maranhão, com 40,0% de casos assintomáticos, relatou 17,5% de letalidade^[@B20]^. Recente estudo em MG encontrou letalidade de 13,5%, porém a frequência relatada de icterícia foi 35,5%^[@B18]^, inferior à do presente estudo (86,5%). Outro surto em MG, no qual 69,4% dos casos foram hospitalizados, encontrou 33,3% de letalidade; em 19 casos classificados como graves (com manifestações hemorrágicas, insuficiência hepatorrenal, prostração intensa ou coma), a letalidade foi de 83,3%^[@B19]^.

Considerando apenas o critério icterícia, 86,5% os casos deste estudo já estariam no mínimo na forma clínica moderada ou grave^[@B1]\ ,\ [@B4]^. Outro estudo descreveu 70% de forma moderada a grave, 69,1% de icterícia e 44,2% de óbitos^[@B15]^.

Não foi observada associação entre óbito e sexo, faixa etária, raça ou cor de pele, escolaridade, ano de notificação, retardo entre início dos sintomas e internação no hospital, dor abdominal e comorbidade. Estudo sobre casos confirmados no Brasil de 2000 a 2012^[@B16]^encontrou letalidade maior no sexo masculino (49,6%) do que no feminino (39,7%), porém a diferença não foi significativa. Estudo de período anterior (1999--2002) encontrou associação significativa da maior chance de óbito como o sexo masculino e a faixa etária acima de 40 anos, mas na análise múltipla sexo e idade perderam a significância^[@B15]^.

A mediana do intervalo entre o início dos sintomas e a admissão no HFSE/IESS (cinco dias) foi um pouco maior do que a de outro estudo (três dias)^[@B19]^. Ambos não encontraram diferenças entre esse intervalo e o óbito, achado concordante com pelo menos outro estudo^[@B18]^. No presente estudo, o primeiro atendimento ocorreu em outras unidades, com encaminhamento posterior para o HFSE/IEISS.

Estudo de MG^[@B18]^relatou tempo de permanência menor do que o deste estudo, também sem diferença segundo o desfecho (média = 5,70 dias e DP = 3,78 dias nos casos de óbito; média = 5,02 dias e DP = 5,88 dias nos sobreviventes). Outro estudo relatou uma mediana do tempo de internação até o óbito de oito dias^[@B19]^, menor do que a nossa. A gravidade dos casos do presente estudo e a utilização de terapia intensiva, hemodiálise e troca plasmática de alto volume são alguns fatores possivelmente relacionados ao maior tempo de permanência e também ao alto custo da assistência.

De forma geral, os valores séricos de transaminases, bilirrubinas, ureia e creatinina deste estudo foram maiores do que os relatados na literatura. Estudo com 36 casos, com 91,7% de formas graves e moderadas^[@B19]^, descreveu para a AST uma variação de 47 a 7.500 U/L (média = 1.027,8); ALT, 26 a 6.600 U/L (média = 815,8); BD, 0,2 a 12,4 mg/dL (média = 3,2); ureia, 10 a 175 mg/dL (média = 56,5); creatinina, 0,6 a 13 mg/dL (média = 2,9). Outro estudo^[@B15]^, com 251 casos e 70,4% de forma moderada a grave, relatou medianas de transaminases menores, embora os valores máximos fossem maiores que os nossos: AST, mediana de 1.096 U/L (variação de 13 a 43.460); ALT, mediana de 957 U/L (9 a 15.250); BD, mediana de 4,7 mg/dL (0,4 a 77,0). Entretanto, para ureia e creatinina, seus valores foram maiores: ureia, mediana de 106 mg/dL (11 a 328); creatinina, mediana de 3,6 mg/dL (1,0 a 19,0).

Tanto no presente estudo como nos dois outros^[@B15]\ ,\ [@B19]^, de forma geral as elevações da AST ultrapassaram as da ALT, o que é descrito na literatura^[@B5]\ ,\ [@B23]^presumivelmente devido ao efeito citopático do vírus no miocárdio e músculos esqueléticos; a ALT é mais específica para doença hepática do que a AST. Quanto ao aumento das bilirrubinas, ocorreu sobretudo, pelo aumento da fração direta, coerente com a literatura^[@B5]^.

Neste estudo, encontrou-se associação significativa entre maiores valores de AST, ALT, BD, ureia e creatinina e óbito, assim como entre menores valores de plaquetemia e óbito. Na análise múltipla, apenas a alteração de excreção renal e a ALT permaneceram significativamente associadas à maior chance de óbito; a AST manteve uma associação com p limítrofe. Outro estudo^[@B15]^encontrou associação com maior chance de óbito para sexo masculino, idade \> 40 anos, icterícia, AST \> 1.200 U/L, ALT \> 1.500 U/L, BT \> 7 mg/dL, BD \> 5 mg/dL e ureia \> 100 mg/dL. Porém, na análise múltipla apenas permaneceram as associações com icterícia e AST \> 1.200 U/L.

Não há tratamento específico até o momento. Recomenda-se a internação das formas graves em hospitais com suporte de terapia intensiva e diálise^[@B1]\ ,\ [@B2]\ ,\ [@B23]^. Alguns antivirais têm sido avaliados, como ribavirina, tiazofurina, carboxamida e compostos pirazolínicos^[@B4]\ ,\ [@B22]^, e mais recentemente o sofosbuvir^[@B7]^. Os eventos terminais catastróficos associados aos casos graves, possivelmente relacionados a uma síndrome de resposta inflamatória sistêmica, representam um campo potencial para avaliação do papel de intervenções como a troca plasmática de alto volume^[@B7]^, que foi realizada na instituição. Essa utilização ocorreu a partir da lógica das diretrizes de manejo da hepatite fulminante; o protocolo usado foi aquele referido por Larsen et al.^[@B24]^, adaptado para as circunstâncias do surto de febre amarela.

O transplante hepático na hepatite fulminante da febre amarela foi realizado pela primeira vez em dezembro de 2017 em São Paulo, não tendo seu papel bem estabelecido^[@B7]\ ,\ [@B23]\ ,\ [@B25]^. No presente estudo, um caso foi transferido para realização de transplante hepático em outra unidade, evoluindo para óbito em menos de 24 horas após a transferência, durante o período transoperatório (óbito incluído neste estudo).

A reemergência da febre amarela fora da região amazônica atingiu regiões próximas a grandes centros urbanos e com população que, em grande parte, não estava imunizada. Nos últimos dois anos, a expansão da doença, principalmente pela região Sudeste, resultou na maior epidemia das últimas décadas. As causas dessa expansão ainda não estão bem esclarecidas; fatores ambientais e alterações do próprio vírus têm sido investigados^[@B7]^. Em 2017, identificou-se uma mutação nas enzimas de replicação viral, mas não se conhece ainda seu impacto^[@B26]^. Estudo recente considera que o vírus da febre amarela responsável pelos surtos de 2016 a 2018 no Sudeste brasileiro pertença a uma linhagem monofilética (BR-YFV_2016/18), provavelmente vinda da região Centro-Oeste para a Sudeste. A sua persistência no Sudeste sugere que essa região apresenta condições ecológicas e climáticas adequadas para a manutenção viral nos períodos epidêmicos e interepidêmicos^[@B27]^. Estação chuvosa prolongada associada a abundância de vetores, desmatamento para agropecuária, transmissão epizoótica e locomoção de indivíduos em período virêmico são fatores citados^[@B4]\ ,\ [@B28]^.

A alta infestação por *Aedes aegypti* em diversos centros urbanos dessas regiões, o aumento do número de casos de febre amarela silvestre e a baixa cobertura vacinal são fatores que favorecem o risco da reurbanização da doença. Os recentes surtos de febre amarela silvestre a partir de dezembro de 2016, atingindo os estados de MG, ES, RJ e SP, e a ocorrência de óbitos confirmados em macacos em outros estados levantaram novamente a relevância da adoção de medidas para reduzir o risco de reurbanização, com alteração nas recomendações de vacinação, incluindo a ampliação das áreas de recomendação da vacina e o início das campanhas com aplicação da dose fracionada^[@B3]\ ,\ [@B7]^.

Nesse contexto, este estudo apresentou a experiência de um hospital que contribuiu de forma expressiva para a assistência aos casos graves de febre amarela do estado. A gravidade da série está representada pelo elevado percentual de icterícia (86,5%), alterações de excreção renal (53,8%) e hemorragias (50,0%), além das elevadas medianas de transaminases séricas observadas. A atenção a esses casos implicou em uma estrutura de complexidade alta, adaptada para responder a uma situação emergencial, que representou um grande desafio para a equipe de saúde. O maior conhecimento do perfil desses casos, sobretudo dos fatores associados à maior chance de óbito, pode colaborar para a discussão do papel de intervenções terapêuticas como a troca plasmática de alta volume. As limitações deste estudo se relacionam principalmente à qualidade da informação oriunda da vigilância epidemiológica, o que foi minimizado pela revisão da investigação e complementação de dados com os prontuários durante o processo de investigação epidemiológica e encerramento dos casos, que faz parte da rotina do serviço de epidemiologia^[@B9]^. O percentual de informações ignoradas foi inferior a 5% para a maioria das variáveis analisadas, à exceção da escolaridade (15,0%) e ureia máxima (7,7%), e muito menores do que em outros estudos^[@B15]^.

A vigilância epidemiológica ativa contribuiu com a notificação ágil às autoridades de saúde, o monitoramento da coleta das amostras para confirmação dos casos e a manutenção de um sistema de informações que, mesmo durante um surto, foi capaz de subsidiar este estudo. O estudo contribuiu para o conhecimento do perfil dos casos de febre amarela no HFSE/IEISS, que internou 17,9% dos casos confirmados no RJ nesse período, com perfil de gravidade alta. Os principais preditores de óbito foram a alteração da excreção renal e a elevação sérica de transaminases, sobretudo ALT. A letalidade elevada reforça a necessidade de diagnóstico e tratamento precoces, e a importância de intensificar a vacinação.

[^1]: Authors' contribution: Study conception and planning: CCE. Data collection, analysis and interpretation: CCE, AGLP, MRVEM, TRAL, RMG, RAM. Text development or review: CCE, AGLP, MRVEM, TRAL, RMG, RAM. Approval of final version: CCE, AGLP, MRVEM, TRAL, RMG, RAM. Public responsibility for study content: CCE, AGLP, MRVEM, TRAL, RMG, RAM.

[^2]: Conflict of interest: The authors declare no conflict of interest.


Second major capex cycle underway as PV industry enters new phase of 100GW-plus annual deployment

Solar PV capital expenditure (capex) covering the midstream segments of the industry (c-Si ingot-to-module and thin-film) is now well into its second major upturn in spending, going into 2018, at a time when the industry is just about to move to a new phase in annual deployment levels of greater than 100GW.

This article discusses why this is happening, the companies and technologies driving this change, and what can be expected in 2018 and beyond.

The underlying themes and outcomes will form a key part of the forthcoming PV CellTech 2018 event in Penang, Malaysia on 13-14 March 2018.

Defining the methodology

PV capex is best analysed by removing spending on polysilicon plants, as the capex here operates on fundamentally different timelines and phasing, compared to capex being allocated to the midstream segment covering ingot-to-module spending. In addition, capex for polysilicon plants is more weighted to plant construction, than discrete process tooling.

The data and graphics contained within this article are generated bottom-up by PV-Tech’s in-house market research business unit that gathers the data for use within its portfolio of syndicated and bespoke research products, in addition to guiding the content and production of the PV CellTech and PV ModuleTech events.

PV capex encompasses also new manufacturing capacity and upgrade equipment spending, in addition to routine maintenance and equipment replacement spending.
Understanding the past

We have gone back 10 years to understand some of the historic trends and drivers that offer some perspective on where the industry stands moving into 2018, and that shape some of the factors that can be used to predict how PV capex will trend over the next 3-5 years.

The figure below shows PV capex trends over the period from 2007 to 2017, referenced to the annual revenues recognized by the leading PV equipment supplier of the past decade, Meyer Burger.

PV capex is going through its second major growth phase, driven by a combination of new capacity expansions, new technology introductions and upgrades to existing installed capacities.

Analysis of PV capex before 2007 is somewhat academic, as spending levels then were minimal. The first real capex cycle for the industry started in the 2007-2009 period, and was driven by a diverse range of issues.

China and Taiwan were then starting their first significant expansion phases for c-Si cell and module capacities, stimulated by demand that was coming from Europe (mostly Spain, Germany and Italy). However, while this was driving huge growth in new order intake from c-Si based tool suppliers, it was thin-film excitement that ultimately drove PV capex levels above USD$10B during 2010 and 2011.

Thin-film market-share gains were being advocated as a done-deal before 2010, and investments of USD$100M at a time were being issued to credible turn-key equipment suppliers, mostly on the back of producing panels that were well below 10% in efficiency. The numbers added up very quickly, and turn-key thin-film production lines quickly had a major influence on overall PV capex levels. Today, none of these lines are in operation.

The spending peak occurred in 2011 and saw literally hundreds of new companies making cells and modules emerge all over China. Each one of these companies saw Europe as a bottomless pit of government subsidy hand-outs that would see crates of Chinese modules shipped in volumes to ports in mainland Europe for years to come.

This didn’t happen. The industry went into chronic overcapacity and oversupply mode, resulting in module pricing collapse. Investor confidence plummeted. Operational losses were widespread. And the result was a collapse in capex in early in 2012.

It took two years for supply and demand to largely get into balance, and this period was all about cost reductions, existing capacity optimization and debottlenecking.

The downturn lasted about two years, and by 2015, green shoots were emerging everywhere with the first signs of technology (not capacity volumes) being the new impetus for the rebound cycle of manufacturing capex.

Technology driven capex rebound

The focus on new technology, both due to upgrades and when incorporated in new fab builds, since 2015 looks very different to the technologies that drove PV equipment spending above $10 billion during 2010 and 2011.

At the c-Si stage, the most obvious change has come from PERC, and by 2019, most of the capacity for both p-type mono and multi will have shifted to include rear passivation deposition, with many of the companies having a clear roadmap to bifaciality. Moving into 2020, this will become mainstream for the industry. Indeed, anyone making c-Si cells with efficiencies below 20% is likely to be left with low-cost selling options then.

However, some of the other key drivers of the current capex rebound are new technology-driven initiatives that have not been seen before, including First Solar’s shift from Series 4 to Series 6 panels and the n-type spending boom that is emerging now in China especially.

It is fair to say that n-type has always seen high levels of interest, with no shortage of roadmaps from major cell producers that tended to be largely wishful thinking. While SunPower and Panasonic largely sat back and watched many n-type start-ups come and go, only Yingli Green and LG Electronics succeeded in having n-type cell capacities in excess of 500 MW that were being operated at mass-production utilization rates.

This all changed about two years ago in China, and the first GW fabs are currently ramping up, with n-type variants spanning n-PERT and heterojunction being the main focus. Regardless of the success rates of these initial movers (many of whom have little if any experience making solar cells until now), what is certain is that we are going to see more investments during 2018 and 2019 with government initiatives in China offering the backdrop for investment security.

In fact, while previous n-type activities in the solar industry were company and R&D lab specific, the China efforts today are more collaborative in nature, or simply less prone to the commercial confidentiality that is the norm for manufacturing outside of China and Taiwan.

Moreover, efforts to use domestic equipment suppliers for n-type tool supply in China further helps to establish (albeit indirectly) an open pool of knowledge that could be shared somewhat freely by other players in China wishing to jump on the n-type bandwagon should it become a competitive threat to p-type mono in coming years.

No sign of Chinese capex slowdown

On so many counts today in the PV industry, not simply for PV capex, there are no obstacles suggesting any imminent cooling in China. The security of a 50GW-plus domestic end-market exclusive to Chinese-produced ingots/wafers/cells/modules is unprecedented, and the fact that we see new technology-driven initiatives now for n-type differentiation should not come as any great surprise.

Investments in a few gigawatts here and there for new n-type projects may seem like reckless extravagance to most outside China struggling to make the numbers balance monthly on established GW-level fabs, but within China this is almost the new norm, and not entirely out of context if one regards the entire c-Si capacity in China as a single integrated manufacturing unit.

The graphic below spells out just how important equipment spending on new capacity and technologies within China has been to the capex rebound since 2015. Remove this contribution, and we are back essentially at 2012 levels.

Equipment spending across the c-Si ingot-to-module value-chain has been stimulated by domestic manufacturing within China, with 2017 and 2018 contributions seeing new efforts to scale up n-type GW fabs.

Going into its third year, PV CellTech 2018 has been structured to address the threat coming from the new n-type investments, and whether in particular n-PERT and heterojunction can truly offer value-added propositions versus p-mono PERC.

This issue will become one of the key themes for solar manufacturing during 2018-2020, as important as the ‘what-next-after-PERC’ question for p-mono. And behind all of this is cost and wafer supply, not to mention potential wafer thickness reduction possibilities not currently being driven by the p-type community.

Could the threat from a few GW of n-type heterojunction capacity in China, coupled with multi-GW of sub-140 micron n-type wafer supply, be the catalyst that finally drives the entire c-Si industry to make a step-wise silicon material consumption decrease that would make major inroads into the silicon component of blended module costs, and cause havoc with polysilicon expansion plans?

PV CellTech 2018 takes place on 13-14 March 2018, in Penang, Malaysia. The relevance of the event, and in mapping out the real technology trends over the next 12-18 months, is almost definitely set to move to a new level of importance.


Q:

Runtime Error: error TS2307: Cannot find module 'leaflet'

I have problem with leaflet dictionary. I saw similar problems on stackoverflow, but it has not been resolved. I reinstalled leaflet and types, but there is still a problem. When I import L from leaflet, i have this problem
I installed leaflet like that npm install leaflet and npm install @types/leaflet
This is line of code where i have problem
import * as L from 'leaflet'

A:

You should use import L from 'leaflet' :)


Ty Van Burkleo

Tyler Lee Van Burkleo (born October 7, 1963) is the current hitting coach for the Cleveland Indians. He is a former bench coach for the Seattle Mariners and a former first baseman in Major League Baseball. He played for two different major league teams in his career: the California Angels () and Colorado Rockies (). He also played for two teams in Japan: the Seibu Lions (–) and the Hiroshima Toyo Carp (). At 24, he was player of the year with the Seibu Lions, hitting 38 home runs and driving in 90 runs for the 1988 Japan Champions.

Biography
Van Burkleo attended Canoga Park High School and Chatsworth High School. He signed a minor league contract for $30,000 with the Milwaukee Brewers in 1981. He was released in 1984 and signed a contract with the Angels' minor league system. He was blocked by Wally Joyner for most of his first stint with the Angels. Van Burkleo's Angels contract was bought by the Seibu Lions of Nippon Professional Baseball in 1987. He was traded to the Hiroshima Toyo Carp in 1991 for cash considerations. Upon returning to the United States for the 1992 season, he signed with the Angels again, then played for the Rockies for two seasons, and in 1996 returned to the Angels for his last playing season.

In 1997, he began his coaching career with the High Desert Mavericks, an Arizona Diamondbacks affiliate. In 2001, he found himself working for the Angels again, as the minor league hitting coordinator. He left the Angels at the end of the 2006 season. For the 2007–2008 seasons, Van Burkleo was the hitting coach for the Oakland Athletics.  In 2009, he was signed by the Mariners to be the bench coach to manager Don Wakamatsu. The following year, he was hired by the Astros to be the minor league hitting coordinator. On August 19, 2012, Van Burkleo was named the interim hitting coach for the Houston Astros. He was named hitting coach of the Cleveland Indians on October 31, 2012, beginning with the 2013 season.

Personal life
He is married to Chris and has five children.

References

External links

Category:1963 births
Category:Living people
Category:American expatriate baseball players in Canada
Category:American expatriate baseball players in Japan
Category:American people of Dutch descent
Category:Baseball players from California
Category:Beloit Brewers players
Category:California Angels players
Category:Cleveland Indians coaches
Category:Colorado Rockies players
Category:Colorado Springs Sky Sox players
Category:Edmonton Trappers players
Category:Hiroshima Toyo Carp players
Category:Lake Elsinore Storm players
Category:Major League Baseball bench coaches
Category:Major League Baseball first basemen
Category:Major League Baseball hitting coaches
Category:Midland Angels players
Category:Nippon Professional Baseball designated hitters
Category:Oakland Athletics coaches
Category:Palm Springs Angels players
Category:Peoria Chiefs players
Category:Redwood Pioneers players
Category:Sportspeople from Oakland, California
Category:Seattle Mariners coaches
Category:Seibu Lions players
Category:Stockton Ports players
Category:Vancouver Canadians players


Community Q&A:

Is mod_rewrite enabled so I can set up Clean URLs in Indexhibit?

I am currently using Indexhibit to manage my website; http://www.indexhibit.org/tutorial/how-to-get-clean-urls/

I wish to create clean URLs as mine are currently messy. As you can see in the link above I have been asked to ask you guys if my server has (Apache) technology called "mod_rewrite" properly setup and enabled for my account to enable me to do this?

Best answer chosen by Web Hosting Hub staff

While looking into this for you, I noticed that you enabled FrontPage extensions for your account. Since you are using Indexhibit for your site, I would recommend removing those extensions by selecting "Uninstall Extensions" in the FrontPage Extensions area of your cPanel account.

Please let us know if you have any additional questions or need further assistance.


<?xml version="1.0" encoding="utf-8"?>
<style xmlns="http://purl.org/net/xbiblio/csl" version="1.0" default-locale="en-US">
  <!-- American Statistical Association, generated from "amstat" metadata at https://github.com/citation-style-language/journals -->
  <info>
    <title>Technometrics</title>
    <id>http://www.zotero.org/styles/technometrics</id>
    <link href="http://www.zotero.org/styles/technometrics" rel="self"/>
    <link href="http://www.zotero.org/styles/american-statistical-association" rel="independent-parent"/>
    <link href="http://amstat.tfjournals.com/asa-style-guide/" rel="documentation"/>
    <category citation-format="author-date"/>
    <category field="math"/>
    <issn>0040-1706</issn>
    <eissn>1537-2723</eissn>
    <updated>2017-07-26T12:00:00+00:00</updated>
    <rights license="http://creativecommons.org/licenses/by-sa/3.0/">This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License</rights>
  </info>
</style>


2 police officers, suspect shot in West Virginia highway shootout

Jan 02, 2015

Lewisburg West Virginia: Two police officers were injured in a New Year's Day shootout after they pulled over two vehicles, one of which was stolen and had two bodies inside, authorities said.The two officers stopped an SUV and a truck around 4 p.m. Thursday on a highway outside of the city, Lt. Michael Baylous of the West Virginia State Police said in a news release. The SUV had a North Carolina license plate that showed it had been stolen.As the officers were conducting the stop, the driver of the truck shot at them with a handgun, wounding both officers, Baylous said. One officer returned f...


.i 50
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.e


One of President Trump Donald John TrumpSteele Dossier sub-source was subject of FBI counterintelligence probe Pelosi slams Trump executive order on pre-existing conditions: It 'isn't worth the paper it's signed on' Trump 'no longer angry' at Romney because of Supreme Court stance MORE’s golf resorts in Scotland will reportedly no longer receive a controversial tax break after a rule change by the Scottish government.

Trump Turnberry, one of Trump’s two luxury golf resorts in the country, received more than £100,000 (about $133,690) in business rates relief this year.

But the Scottish government announced that beginning next year, properties must have a “rateable value” of less than £1.5 million to be eligible for the tax break, according to the Sunday Herald. The Trump Turnberry’s rateable value is just over £1.6 million, or about $2.1 million.

Trump’s other golf property in Scotland does not qualify for the rebate, which is intended to help struggling businesses.

According to the report, this rule change will likely be seen as an intentional affront to Trump, with whom the Scottish National Party, which is currently in power, has a tense relationship.

ADVERTISEMENT

Scottish politicians praised the move, saying that Scottish taxpayers should not have to support Trump's businesses.

Patrick Harvie, a member of Scottish Parliament from the Green Party, told the Herald that “it’s bad enough that [Trump] has a business presence in Scotland.”

“It’s galling to learn that the public purse is giving him a helping hand,” he said. “His brand is toxic and Scotland is better off without any association with him or his businesses. Tax relief should go to folk who really need it.”

The Turnberry has been a source of controversy for Trump and the Scottish government. He has long opposed wind farms in the U.K., particularly one located near the golf course.

And the head of the Scottish Open said earlier this year that although the Turnberry was being considered to host the open in future years, Trump’s divisive politics have forced them to reconsider.


Q:

Why haven't jurists corrected the ambiguity of 'civil law'?

Source: A Brief Introduction to Law in Canada (Mar. 2017). p. 39 Bottom. Box 2.3.

"Common Law" and "Civil Law": Alternate Meanings
As we have seen, some legal expressions have different meanings in different contexts. It addition
to referring to legal systems, the phrases "common law" and "civil law" can have other meanings, too.
  The phrase civil law is sometimes used as a synonym for private law—in other words, laws governing the relationship between persons (as opposed to public law, which deals with the legal relationship between a state and its individual members). Private and public law are generally
recognized distinctions in both common law and civil law systems (except perhaps in some so-cialist countries). Therefore, somewhat confusingly, there could be a reference to civil law (where
the context means private law) and its application in a common law jurisdiction. Adding to the
confusion is the fact that in many civil law countries, their civil codes are primarily concert*d with
private, or civil, law matters as opposed to public law ones. Criminal law and other areas of public law are frequently dealt with in other "non-code" statutes. However, the key features of civil law
systems—such as the inquisitorial approach of judges and the lack of precedent—usually apply
to these legislated areas as well.
  The phrase common law, apart from its reference to the legal system that originated in England.
can also refer to decisions by courts exercising their "common law" jurisdiction (used in contradistinction to decisions by courts exercising their "equitable" jurisdiction), and to case law generally
(used in contradistinction to legislation, or enacted laws).

This polysemy of 'civil law' (e.g. our "civil-law" tag) can be easily untangled, if 'civil law' is restricted to mean only private law OR only continental law, or if 'civil law' is abandoned and overriden with the latter two terms.
So why haven't jurists (lawyers and judges) done so?

A:

The English language does not have the equivalent of the French Academy to officially regulate questions of spelling, grammar, punctuation and word meaning.
Jurists don't control how the language is used and for the most point don't bother to try to do so. Also, context almost always clarifies this particular ambiguity.


/*-
 * See the file LICENSE for redistribution information.
 *
 * Copyright (c) 2002, 2015 Oracle and/or its affiliates.  All rights reserved.
 *
 */

package com.sleepycat.persist.impl;

/**
 * Base class for EntityInput implementations.  RecordInput cannot use this
 * base class because it extends TupleInput, so it repeats the code here.
 *
 * @author Mark Hayes
 */
abstract class AbstractInput implements EntityInput {

    Catalog catalog;
    boolean rawAccess;

    AbstractInput(Catalog catalog, boolean rawAccess) {
        this.catalog = catalog;
        this.rawAccess = rawAccess;
    }

    public Catalog getCatalog() {
        return catalog;
    }

    public boolean isRawAccess() {
        return rawAccess;
    }

    public boolean setRawAccess(boolean rawAccessParam) {
        boolean original = rawAccess;
        rawAccess = rawAccessParam;
        return original;
    }
}


Q:

RTC post-build deliver option with Jenkins build

Is it possible to execute a Post-build Deliver when using Jenkins server with RTC source?
This is my process;

When a job is started Jenkins connects to RTC Source using the Rational Team Concert plugin and fetches the required code. (Connects to RTC using a build definition which contains details of the workspace to use. This build definition also contains details of the post-build steps)
Jenkins tests/builds/deploys application
Job completes with a status of success.

When I open the results view for the build definition associated with this Jenkins job i notice the absence of any post-build delivery information in the Contribution Summary.
Using the setup I've mentioned should Post-build Delivery be possible?

A:

@niloc,
The ability to initiate a post-deliver option currently only exists in JBE (Jazz Build Engine).  There currently is an enhancement open to improve this for the Team Concert Plugin for Hudson/Jenkins ... Teamconcert plugin to trigger Post-Build Events configured in RTC Build Definition.
However, Heather describes a work around in a comment on 05/Dec/13.
Scott


With the news earlier this year that The Cooper Union in New York will, for the first time in 155 years, begin charging tuition fees to students in 2014, the existing students at its Irwin S. Chanin School of Architecture are taking steps to ensure that it stays true to the meritocratic principles on which it was founded. To achieve this, they have launched the One Year Fund, an attempt to crowdsource $600,000 in order to cover the tuition fees of the incoming students in 2014.

Read more about the One Year Fund, and how it fits into the students' larger aims, after the break.

From their campaign, it is clear the students feel that not having to pay tuition is fundamental to the nature of Cooper Union, and gives an important aspect to their education as architects. "Charging tuition adds money to the equation and changes the relationships that are already in place", says one student. In their press release, they state "it is imperative to ensure that future students are educated under the same meritocratic conditions as they are today and have been for the past 155 years."

Raising $600,000 in 40 days may be an ambitious goal, but it is a vital step in preserving what they see as a vital element of the education of future students. This first step is a temporary solution, simply aiming to provide "one full year to develop and put into action another financial model to preserve the Cooper Union and its fundamental principles."

If the principle of a free, meritocratic education for architects is an idea you would like to support, you can donate on their fundraising page. you can also connect with the One Year Fund via Facebook and Twitter.