geolocation and remote sensing technologies are increasingly being applied to the mapping and spatial analysis of infectious diseases , including lymphatic filariasis   and malaria . for such maps to reflect the real pattern of infection or disease ,
lymphatic filariasis and malaria are both currently subject to renewed control programmes , and share anopheline vectors in some parts of the world .
filariasis is being targeted for elimination , but reduction in its infection intensity could conceivably , via the removal of infection - induced vector mortality , lead to more efficient transmission of malaria .
accurate mapping of the two infections can help monitor their control , including the detection of any unwanted interactions .
here , we present spatial analysis of both parasites in the same area of papua new guinea , using a recently developed technique which estimates the scale of variation , taking into account the typically highly skewed distribution of parasite counts . in a rural area of the east sepik province ,
cross - sectional parasitological surveys were done of the population aged over five years , as part of a trial of diethylcarbamazine ( dec ) plus ivermectin versus dec alone against lymphatic filariasis .
although , with regard to malaria , the lower age threshold is a limitation , in the nearby wosera area , peak prevalence was not reached till after five years .
wuchereria bancrofti microfilariae were counted microscopically on nuclepore filters , through which 1 ml of night - collected blood had been passed .
anopheles mosquitoes , predominantly anopheles punctulatus s.s . , are the vectors of filariasis in the area .
villages are divided into subunits , which we call hamlets , distinguished by names in the local languages .
these were mapped with a hand - held trimble ensign global positioning system ( gps ) machine . in the 1994 survey , immediately before the first round of treatment , blood samples were obtained from 2,219 people in 149 hamlets .
hamlets whose distance to their nearest neighbour was , due to gps inaccuracy , measured as less than 10 m were combined with their nearest neighbour .
there were two such instances , so reducing the total number of hamlets to 147 .
as described elsewhere , spatial structure in the infection densities was fitted by a negative binomial model .
the mean density is fitted as a log - linear function of age , sex , and the hamlet mean . in turn , the hamlet means are given a spatial structure , with closer hamlets being more highly correlated . specifically , hamlet i adds a ' hamlet effect ' ui to the logarithm of the mean density .
when exponentiated , these are similar to standardized mortality ratios ( smrs ) although relate to parasite densities rather than death rates , so can be called standardized parasite density ratios .
these age- and sex - adjusted hamlet effect uil have a covariance matrix ( 1/)exp(-dil/ ) , where dil is the distance between hamlet i and l. the parameter  measures the scale of spatial correlation .
more specifically , loge2 is the distance over which the correlation reduces by half , which we call the ' half - distance ' .
the process can also be thought of a smoothing process of the raw hamlet means , adjusting for age and sex , and with a large spatial scale (  ) corresponding to a greater degree of smoothing .
the model was fitted by programs written in the c and fortran languages , and checked in terms of ability to represent the spatial variability , and robustness to distributional assumptions . at the individual level , the mean pre - treatment microfilaraemia density ( including zeros ) increased with age , till reaching 1591 mf / ml in the 4049 year age group , then flattening out .
the mean p. falciparum density was 18 asexuals per 200 white cells in those aged 510 years , decreasing to below 2 for ages over 30 years . at the hamlet level ,
the median of the crude hamlet - specific pre - treatment mean microfilarial densities was 552 mf / ml , range 04625 . for p.
falciparum , the median was 2.2 asexual parasites per 200 white cells , range 0113 .
the figure shows the spatial variation in the pre - treatment density of both parasites in this area , estimated from the model , taking into account age and sex effects , and spatial correlation .
w. bancrofti had an estimated half - distance of 1.7 km ( = 2.41 , = 1.79 ) .
p. falciparum showed virtually no spatial correlation , the half - distance being just 14 m ( = 0.0208 , = 1.13 ) , around the resolution limit of the gps .
spatial variation of a ) w. bancrofti and b ) p. falciparum in parts of urim and urat census districts , east sepik province .
the scale is in kilometres with an arbitrary origin near the centre of the study area ( 142.7e , 3.6s ) .
each hexagon represents one hamlet , with the shading showing the quartile of the standardized parasite density ratio . for w. bancrofti ,
the 0 , 25 , 50 , 75 and 100th percentiles are 0.27 , 0.56 , 1.02 , 1.71 and 4.3 respectively . for p. falciparum
the curve plotted against the vertical axis shows the rate at which correlation in mean parasite density decays with distance .
the solid lines in the body of the map show unpaved roads , and the dashed line indicates the division of villages between the two census districts .
one year after the first round of mass treatment with anti - filarial drugs ( coverage 88% ) , all 14 randomized clusters showed a reduction in williams mean w. bancrofti density , ranging from 47 to 96% , mean 80% .
all 14 clusters showed an increase in williams mean p. falciparum , the increases ranging from 2 to 255% , mean 91% .
however , although dec+ivermectin was more effective against w. bancrofti , no tendency was seen for those clusters to have larger increases in p. falciparum : in 3 of the 7 pairs the dec+ivermectin cluster had the larger increase , with 4 having the opposite tendency .
to further investigate the possibility that this increase was due to the treatment , the results of the spatial models were put into a hamlet - level analysis : an ' ecological ' analysis in epidemiological terms .
the difference in the post- and pre - treatment hamlet effects was calculated for both filariasis and malaria , and a linear relation tested using the pearson correlation coefficient .
there was negligible correlation between the changes in the densities of the two infections ( r = 0.026 , p = 0.75 ) .
the world health organization methodology of ragfil ( rapid assessment of the geographical distribution of bancroftian filariasis ) is based on a 50  50 km grid .
gyapong et al . have compared this to a finer 25 km grid in ghana , with both leading to operationally similar conclusions .
when extended to three other countries of west africa , the method showed filariasis to have an unexpectedly wide geographical distribution .
the current results suggest that , at the opposite end of the spatial scale , it may be possible for foci to persist within the interstices of a 50  50 km grid , or even a 25  25 km one ; a conclusion similar to that reached by srividya et al . in india .
however , the overall importance of any such effects will also depend on the relative magnitudes of variation at different scales , which we are unable to measure beyond the extent of our current study area .
the need for accurate geographical monitoring may increase if the current elimination campaign reduces filariasis over a wide scale and proceeds from an ' attack ' to a ' consolidation ' phase ( to borrow malaria eradication terminology ) .
for example , thompson et al . , found the risk of malaria varying by a factor of 6 over 500 m .
however , the scale of variation found in the current study was still smaller than expected , with even the closest hamlets showing little correlation .
the much smaller scale of variation of malaria is probably related to its rapid variation over time . by comparison
, the risk of acquiring w. bancrofti infection per mosquito bite seems to be much smaller , but infections can last much longer .
a single cross - sectional survey therefore reflects a longer - term aggregate of filariasis exposure history .
our estimation of the hamlet effects can be seen as a smoothing method , in which the degree of smoothing is determined by the data . in this example , the west - east trend in filariasis density was not easily discernible in the raw data , while the low spatial correlation of malaria meant that the smoothed map is similar to the crude one .
any pattern presumably reflects spatial variation in factors which affect the parasite , vector or host , but which are not included in the model . in the current study ,
such factors are likely to include those related to vector density , such as distance to breeding sites , but this information is not available for the whole study area , and the lack of pattern in malaria infection suggests that other factors must also be involved .
we view the technique as potentially useful in identifying such factors , as well as identifying ' hot spots ' of infection .
our method takes account of the extreme skewness shown by most parasite distributions , which can cause problems even at the exploratory stage of analysis .
for example , we found that using the common log(x+1 ) transformation to plot the hamlet ' geometric means ' induced a spurious spatial correlation in malaria infection .
excess mosquito mortality caused by w. bancrofti would make it feasible for filariasis control to enhance malaria transmission .
an ' ecological ' analysis did not show such an effect in this study , but monitoring should continue in those areas where anopheles are vectors of both infections . for
the elimination of filariasis , mapping at small as well as large scales will be necessary , including urban areas , especially as efforts proceed beyond the ' attack ' phase .
dec diethylcarbamazine gps global positioning system ragfil rapid assessment of the geographical distribution of bancroftian filariasis smr standardized mortality ratio
the work originated in a drug trial of which james kazura and michael alpers were the co - principal investigators , and which was led in the field by phil hyun and zachary dimber .
neal alexander worked on the drug trial and , for this paper , made the gps readings and wrote the first draft .
moses bockarie also contributed to the trial , including ensuring that the blood slides were read .
the spatial model was initially developed by neal alexander under the supervision of bryan grenfell .
the model was finalized by neal alexander , rana moyeed and julian stander , and fitted by programs written by rana moyeed and julian stander .
the drug trial was supported financially by the world health organization ( grant number tdr 910466 ) and the government of papua new guinea .
julian stander was partially supported by the european union tmr network erb - fmrx - ct96 - 0095 .
bryan grenfell was supported by the wellcome trust and the biotechnology and biological sciences research council .
 the spatial variation of wuchereria bancrofti and plasmodium falciparum infection densities was measured in a rural area of papua new guinea where they share anopheline vectors . 
 the spatial correlation of w. bancrofti was found to reduce by half over an estimated distance of 1.7 km , much smaller than the 50 km grid used by the world health organization rapid mapping method . for p. falciparum , negligible spatial correlation was found . 
 after mass treatment with anti - filarial drugs , there was negligible correlation between the changes in the densities of the two parasites . 
Findings
List of abbreviations
Competing interests
Authors' contributions
Acknowledgements