  we conducted a cross - sectional seroprevalence study among 1,227 persons from the mbeya region in southwestern tanzania to estimate tgr seroprevalence rates and to assess associated sociodemographic and environmental risk factors .
this study was conducted as a substudy within the emini ( evaluation and monitoring the impact of new interventions ) longitudinal cohort study .
briefly , in 2005 we conducted a census at 9 study sites ( figure ) to collect baseline data , and 10% of census households were chosen by geographically stratified random selection to participate in the 5-year emini longitudinal cohort study ( http://www.mmrp.org/projects/cohort-studies/emini.html ) . from these , serum specimens for this substudy were selected by stratified disproportionate random sampling of stored samples from 17,872 persons who took part in the second emini survey in 2007 .
stratification was done for age ( 7 categories ) , altitude of residence ( 2 categories ) , and ownership of domestic mammals ( 2 categories ) and resulted in 28 strata of roughly similar size , described in detail elsewhere ( 8) .
serum samples were tested for igg against r. typhi by indirect immunofluorescence assay ( iifa ) with the same batch of a commercially available test ( rickettsia typhi spot if ; fuller laboratories , fullerton , ca , usa . ) . samples with an igg titer of > 64 or higher were regarded as positive ; because iifa for antibody testing against rickettsiae has a high sensitivity and specificity , as shown by different researchers and with different antigen preparations ( 9 ) .
comparison of the commercial iifa with a commercial elisa in our laboratory confirmed this approach ( g. dobler , unpub .
study sites in tanzania , showing positivity and negativity for igg against rickettsia typhi displayed in voronoi polygons .
numbers in parentheses indicate site prevalence . to identify possible risk factors for tgr igg positivity , we analyzed seropositivity as the binary outcome of uni- and multivariable poisson regression models with robust variance estimates adjusted for household clustering .
initial univariable models for all factors that we deemed as possibly related to tgr infection ( table ) were used to identify variables with a univariable p value < 0.1 for further multivariable evaluation .
stepwise backward and forward regression , the akaike and bayesian information criteria , and various assessments of model fit were used to identify the best multivariable model , in which only variables with a multivariable p value < 0.1 were retained . * pr , prevalence ratio ; ses , socioeconomic status .
blank cells indicate that the variables were not included in the multivariable analyses due to lack of multivariable significance . 
results of univariable and multivariable poisson regression adjusted for household clustering by using robust variance estimates . 
results of separate models for each of the covariates below .   multivariable model ,
including only age , distance to nearest highway , and enhanced vegetation index as covariates . 
ses rank , rank ( from 0 [ lowest ] to 10 [ highest ] ) , according to socioeconomic score . of the 1,227 analyzed serum specimens , 114 specimens ( 9.3% )
this finding translates into an estimated overall population prevalence of 8.4% ( 95% ci 6.8%10.1% ) when findings are extrapolated from our stratified sample to the underlying population of the 9 sites by using direct standardization .
we found local maximum prevalence in the urban sites , ruanda ( 17.5% ) and iyunga ( 17.8% ) , and in semiurban mlowo ( 12.5% ; figure ) .
the highest seropositivity rate was found in the age quintile from 42.1 to 55.2 years , with a decline thereafter . in univariable analysis
, several environmental covariates showed a significant inverse association with tgr igg ( table ) , which included vegetation density , rainfall , minimum and night temperatures , whereas population density , cattle density , and socioeconomic status were positively associated with seropositivity .
the geographic distribution of seropositive participants ( figure ) led us to include distance to the nearest highway as a variable in the analysis .
the final multivariable model included age , vegetation density , and distance to the nearest highway as significant predictors of tgr igg .
other factors were not included in the multivariable model because their lack of multivariable significance .
although significant in univariable analysis , the association of population density , rainfall , socioeconomic status , and cattle density became nonsignificant in the multivariable model when vegetation density was included ( p = 0.66 for population density ; data not shown ) . other factors , including sex , livestock ownership , day and night average land surface temperatures , and other environmental factors , were unrelated to tgr seropositivity .
in contrast to results of a recent study of febrile patients from inland northern tanzania ( 6 ) , site - specific seropositivity prevalences of up to 17.8% in our study suggest that tgr contributes substantially to febrile illness in some areas of the mbeya region .
our study provides data on environmental risk factors for tgr seropositivity , which might be useful to inform a predictive model for disease occurrence .
the inverse association of vegetation density with seropositivity has been described for plague in uganda , a disease that is also transmitted by the rat flea ( x. cheopsis ) ( 10 ) .
that study and early laboratory data suggest that dryness is not the driving factor behind the link between vegetation and disease transmission , because increasingly dry conditions in the laboratory adversely affect vector lifespan ( 11 ) . in our study ,
the urbanity of a settlement , expressed by population density and closeness to highways , may still be a relevant factor through providing more favorable habitats for the mammal reservoir hosts , and sparse vegetation could just be a proxy for urbanization .
the positive univariable association of seropositivity with socioeconomic status appears to be a product of the higher socioeconomic status in urbanized communities .
additional research is needed to detect the pathogen in acute infection and to describe the local transmission cycle to validate the identified risk factors prospectively .
we further hypothesize that remote sensing data could be used to design a model for prediction of r. typhi infection , which could be used to direct public health interventions in the future .
 rickettsioses caused by typhus group rickettsiae have been reported in various african regions . 
 we conducted a cross - sectional survey of 1,227 participants from 9 different sites in the mbeya region , tanzania ; overall seroprevalence of typhus group rickettsiae was 9.3% . 
 risk factors identified in multivariable analysis included low vegetation density and highway proximity . 
The Study
Conclusions 