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      Impact of preexisting dengue immunity on Zika virus emergence in a dengue endemic region

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          Abstract

          The clinical outcomes associated with Zika virus (ZIKV) in the Americas have been well documented, but other aspects of the pandemic, such as attack rates and risk factors, are poorly understood. We prospectively followed a cohort of 1453 urban residents in Salvador, Brazil, and, using an assay that measured immunoglobulin G3 (IgG3) responses against ZIKV NS1 antigen, we estimated that 73% of individuals were infected during the 2015 outbreak. Attack rates were spatially heterogeneous, varying by a factor of 3 within a community spanning 0.17 square kilometers. Preexisting high antibody titers to dengue virus were associated with reduced risk of ZIKV infection and symptoms. The landscape of ZIKV immunity that now exists may affect the risk for future transmission.

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          Human antibody responses after dengue virus infection are highly cross-reactive to Zika virus.

          Zika virus (ZIKV) is an emerging mosquito-borne flavivirus of significant public health concern. ZIKV shares a high degree of sequence and structural homology compared with other flaviviruses, including dengue virus (DENV), resulting in immunological cross-reactivity. Improving our current understanding of the extent and characteristics of this immunological cross-reactivity is important, as ZIKV is presently circulating in areas that are highly endemic for dengue. To assess the magnitude and functional quality of cross-reactive immune responses between these closely related viruses, we tested acute and convalescent sera from nine Thai patients with PCR-confirmed DENV infection against ZIKV. All of the sera tested were cross-reactive with ZIKV, both in binding and in neutralization. To deconstruct the observed serum cross-reactivity in depth, we also characterized a panel of DENV-specific plasmablast-derived monoclonal antibodies (mAbs) for activity against ZIKV. Nearly half of the 47 DENV-reactive mAbs studied bound to both whole ZIKV virion and ZIKV lysate, of which a subset also neutralized ZIKV. In addition, both sera and mAbs from the dengue-infected patients enhanced ZIKV infection of Fc gamma receptor (FcγR)-bearing cells in vitro. Taken together, these findings suggest that preexisting immunity to DENV may impact protective immune responses against ZIKV. In addition, the extensive cross-reactivity may have implications for ZIKV virulence and disease severity in DENV-experienced populations.
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            Impact of Environment and Social Gradient on Leptospira Infection in Urban Slums

            Introduction At present, one billion of the world's population resides in slum settlements [1]. This number is expected to double in the next 25 years [1]. The growth of large urban populations which are marginalized from basic services has created a new set of global health challenges [2],[3]. As part of the Millennium Development Goals [4], a major priority has been to address the underlying poor sanitation and environmental degradation in slum communities which in turn, are the cause of a spectrum of neglected diseases which affect these populations [2],[3],[5]. Leptospirosis is a paradigm for an urban health problem that has emerged due to recent growth of slums [6],[7]. The disease, caused by the Leptospira spirochete, produces life-threatening manifestations, such as Weil's disease and severe pulmonary hemorrhage syndrome for which fatality is more than 10% and 50%, respectively [7]–[9]. Leptospirosis is transmitted during direct contact with animal reservoirs or water and soil contaminated with their urine [8],[9]. Changes in the urban environment due to expanding slum communities has produced conditions for rodent-borne transmission [6],[10]. Urban epidemics of leptospirosis now occur in cities throughout the developing world during seasonal heavy rainfall and flooding [6], [11]–[18]. There is scarce data on the burden of specific diseases that affect slum populations [2], however leptospirosis appears to have become a major infectious disease problem in this population. In Brazil alone, more than 10,000 cases of severe leptospirosis are reported each year due to outbreaks in urban centers [19], whereas roughly 3,000, 8,000 and 1,500 cases are reported annually for meningococcal disease, visceral leishmaniasis and dengue hemorrhagic fever, respectively, which are other infectious disease associated with urban poverty [20]–[22]. Case fatality (10%) from leptospirosis [19] is comparable to that observed for meningococcal disease, visceral leishmaniasis and dengue hemorrhagic fever (20%, 8% and 10%, respectively) in this setting [20],[23],[24]. Furthermore, leptospirosis is associated with extreme weather events, as exemplified by the El Niño-associated outbreak in Guayaquil in 1998 [25]. Leptospirosis is therefore expected to become an increasingly important slum health problem as predicted global climate change [26],[27] and growth of the world's slum population [1] evolves. Urban leptospirosis is a disease of poor environments since it disproportionately affects communities that lack adequate sewage systems and refuse collection services [6],[10],[11]. In this setting, outbreaks are often due to transmission of a single serovar, L. interrogans serovar Copenhageni, which is associated with the Rattus norvegicus reservoir [6], [28]–[30]. Elucidation of the specific determinants of poverty which have led to the emergence of urban leptospirosis is essential in guiding community-based interventions which, to date, have been uniformly unsuccessful. Herein, we report the findings of a large seroprevalence survey performed in a Brazilian slum community (favela). Geographical Information System (GIS) methods were used to identify sources for Leptospira transmission in the slum environment. Furthermore, we evaluated whether relative differences in socioeconomic status among slum residents contributed to the risk of Leptospira infection, in addition to the attributes of the environment in which they reside. Methods Study site and population The study was conducted in the Pau da Lima community (Figure 1A) which is situated in the periphery of Salvador, a city of 2,443,107 inhabitants [31] in Northeast Brazil. Pau da Lima is a region of hills and valleys, which was a sparsely inhabited area of Atlantic rain forest in the 1970s and subsequently transformed into a densely-populated slum settlement (Figure 1B) due to in-migration of squatters. In total, 67% of the population of Salvador and 37% of the urban population in Brazil reside in slum communities with equal or greater levels of poverty as that found in Pau da Lima [32],[33]. 10.1371/journal.pntd.0000228.g001 Figure 1 Slum community site in the city of Salvador, Brazil. (A) The yellow line in the aerial photograph is the boundary of the study site in the Pau da Lima community. The map in the bottom left corner shows the location of Salvador in Brazil and the study site (red) within the city. (B) Photograph of the typical environment at the community study site, which shows a valley in which households is situated and the proximity of households to open sewers and refuse. (C) Close-up view of the orthomap used to georeference households (red and black dots) and environmental attributes, such as open sewers (blue line) and refuse deposits, for the region marked as a yellow box in Panel A. The red arrow represents the direction from which the photograph in Panel B was taken. A study site was established which comprised of four valleys in an area of 0.46 km2 (Figure 1A). Active hospital-based surveillance found that the mean annual incidence of severe leptospirosis was 57.8 cases per 100,000 population at the study site between 1996 and 2001 (unpublished data). The study team conducted a census during visits to 3,689 households within the site in 2003 and identified 14,122 inhabitants. Households were assigned sequential numbers. A computer-based random number generator was used to select a list of 1,079 sample households from a database of all enumerated households. Eligible subjects who resided in sample households and had five or more years of age were invited to be a study participant. Subjects were enrolled into the study between April 2003 and May 2004 according to written informed consent approved by the Institutional Review Boards of the Oswaldo Cruz Foundation, Brazilian National Commission for Ethics in Research, and Weill Medical College of Cornell University. Household survey The study team of community health workers, nurses and physicians conducted interviews during house visits and administered a standardized questionnaire to obtain information on demographic and socioeconomic indicators, employment and occupation, and exposures to sources of environmental contamination and potential reservoirs in the household and workplace. Responses reported by subjects were used to obtain information on race. The study team evaluated literacy according to the ability to read standardized sentences and interpret their meaning. Informal work was defined as work-related activities for which the subject did not have legal working documents. The head-of-household, defined as the member who earned the highest monthly income, was interviewed to determine sources and amounts of income for the household. Subjects were asked to report the highest number of rats sighted within the household property and the site of work-related activities. The study team surveyed the area within the household property to determine the presence of dogs, cats and chickens. Geographical Information System (GIS) survey An ArcView version 8.3 software system (Environmental Systems Research Institute) database was constructed with georeferenced aerial photographs and topographic maps provided by the Company for Urban Development of the State of Bahia (CONDER). Photographs of the study site, which had a scale of 1∶2,000 and spatial resolution of 16cm, were taken in 2002. During the census, the study team identified households within the study site and marked their positions onto hard copy 1∶1,500 scale maps (Figure 1C), which were then entered into the ArcView database. A survey was conducted during the seasonal period of heavy rainfall between April and August 2003 to geocodify the location of open sewage and rainwater drainage systems. During three time points within this period, the study team mapped the sites of open accumulated refuse and measured the area of these deposits. Mean values for areas of refuse deposits were calculated and used for the analyses. Serological analysis Sera were processed from blood samples collected from subjects during house visits. The microscopic agglutination test (MAT) was performed to evaluate for serologic evidence of a prior Leptospira infection [34]. A panel of five reference strains (WHO Collaborative Laboratory for Leptospirosis, Royal Tropical Institute, Holland) and two clinical isolates [6] were used which included L. interrogans serovars Autumnalis, Canicola and Copenhageni, L. borgspetersenii serovar Ballum, and L. kirschneri serovar Grippotyphosa. The use of this panel had the same performance in identifying MAT-confirmed cases of leptospirosis during surveillance in Salvador [6],[16] as did the WHO recommended battery of 19 reference serovars [34]. Screening was performed with serum dilutions of 1∶25, 1∶50 and 1∶100. When agglutination was observed at a dilution of 1∶100, the sample was titrated to determine the highest titer. Statistical methods Information for subjects was double entered into an EpiInfo version 3.3.2 software system (Centers for Diseases Control and Prevention) database. Chi-square and Wilcoxon rank sum tests were used to compare categorical and continuous data, respectively, for eligible subjects who were and were not enrolled in the study. A P value ≤0.05 in two sided testing was used as the criterion for a significant difference. Preliminary analyses evaluated a range of MAT titers as criteria for prior Leptospira infection and found that the use of different cut-off values (1∶25–1∶100) identified similar associations with respect to the spatial distribution of seropositive subjects and risk factors for acquiring Leptospira antibodies. A titer greater or equal to 1∶25 was therefore used to define the presence of Leptospira antibodies in the final analyses. The presumptive infecting serovar was defined as the serovar against which the highest agglutination titre was directed [34]. Crude prevalence rates were reported since age and gender-adjusted values did not differ significantly from crude values. Ninety-five percent confidence intervals (CI) were adjusted for the cluster sampling of households. Kernel density estimation analysis was performed with a range of bandwidths (10–120 meters) to evaluate smoothed spatial distributions of subjects with Leptospira antibodies and all subjects. The R version 2.4.1 statistical package (R Foundation for Statistical Computing) was used to obtain estimates which were adjusted for boundary effects. The ratio of the Kernel density estimators for subjects with Leptospira antibodies and all subjects was measured to determine the smoothed population-adjusted risk distribution. A digital terrain model of topographic data was used (ArcGIS 3D Analyst Extension software) to obtain continuous estimates of altitude for the study area. The distances, calculated in three-dimensional space, of households to nearest open drainage systems and refuse deposits were evaluated as proxies of exposure to these sources of environmental attributes. Elevation of households with respect to the lowest point in the valley in which they were situated was used as a surrogate for flood risk. Generalized additive models (GAM) [35] were used to evaluate the functional form of the association between continuous variables and the risk of acquiring Leptospira antibodies. When indicated, continuous variables were categorized in multivariate analyses according to the x-intercept value observed in the plots of fitted smoothed values. We used Poisson regression [36] to estimate the effect of demographic, socioeconomic, household and workplace-related factors on the prevalence of Leptospira antibodies. A Bayesian inference approach was used which incorporated two random effects in order to account for overdispersion and cluster sampling within households. This approach has been used to estimate parameters in complex models [37] and is less sensitive to sparse data [38]. Standard non-informative prior distributions were used in models which were fitted with WinBUGS version 1.4.2 (MRC Biostatistics Unit). In multivariate analysis, all variables which had a P value below 0.10 in univariate analyses were included in the initial model. In order to address co-linearity among variables, we identified sets of covariates with the high Spearman correlation coefficients (>0.3 or 44 years, respectively). However, 8.3% (95% CI 6.2–10.5) of children 5–14 years of age had evidence for a prior exposure to Leptospira. The prevalence was higher in males than females (17.8 versus 13.6%, respectively; PR 1.32, 95% CI 1.10–1.57) (Table 1). Similar associations with age and gender were observed when MAT titers of ≥1∶50 and ≥1∶100 were used to define subjects with Leptospira antibodies. 10.1371/journal.pntd.0000228.t001 Table 1 Risk factors for Leptospira antibodies among subjects at the slum community site. Variables Leptospira antibodies PR (95% CI) Yes (n = 489) No (n = 2,682) Univariatea Multivariateb No. (%) or median (IQR) c Demographic Age, years 05–14 71 (15) 781 (29) 1.00 1.00 15–24 136 (28) 704 (26) 1.98 (1.47–2.61) 2.02 (1.50–2.69) 25–34 122 (25) 524 (20) 2.31 (1.71–3.07) 2.54 (1.86–3.41) 35–44 73 (15) 350 (13) 2.11 (1.50–2.88) 2.24 (1.59–3.08) ≥45 87 (18) 323 (12) 2.60 (1.88–3.51) 2.92 (2.10–4.00) Male gender 247 (51) 1140 (43) 1.32 (1.10–1.57) 1.38 (1.14–1.64) Socioeconomic indicators Black raced 169 (35) 724 (27) 1.35 (1.11–1.62) 1.25 (1.03–1.50) Household per capita income, US$/day 1.14 (0.39–1.88) 1.30 (0.61–2.20) 0.91 (0.85–0.97)e 0.89 (0.82–0.95)e Did not complete primary school 394 (81) 2018 (75) 1.32 (1.04–1.65) - Household factors Time of residence in household, years 8 (3–17) 7 (3–12) 1.02 (1.01–1.03)e - Level above lowest point in valley, meters 18.78 (8.59–31.05) 24.71 (13.00–36.04) 0.99 (0.98–0.99)e - Distance from an open sewer, meters 14.95 (7.34–31.00) 21.04 (8.99–38.11) 0.99 (0.99–1.00)e - Distance of household from an open sewer/lowest point in valley ≥20 m/≥20 m 158 (32) 1198 (45) 1.00 1·00 ≥20 m/ 2 rats 256 (52) 1039 (39) 1.60 (1.33–1.91) 1.32 (1.10–1.58) Dog 231 (47) 1028 (38) 1.36 (1.14–1.62) - Chicken 227 (46) 988 (37) 1.40 (1.17–1.66) 1.26 (1.05–1.51) Cat 106 (22) 406 (15) 1.44 (1.15–1.77) - Work-related exposures Informal work 157 (32) 637 (24) 1.42 (1.17–1.71) - Contact with contaminated environmentg 83 (17) 284 (11) 1.57 (1.22–1.96) - Risk occupationh 49 (10) 127 (5) 1.90 (1.37–2.51) - a Univaritate prevalence ratios (PR) and 95% confidence intervals (CI) are shown for variables which were significant (P<0.05) in the univariate analyses. b Multivariate PR and 95% CI are shown for covariates which were included in the final best fit Poisson regression model. c Numbers and percentages are shown for categorical variables. Median and interquartile range (IQR) are shown for continuous variables of per capita household income, time of residence in study household, level above lowest point in valley and distance from an open sewer and refuse deposit. d Data is missing for two non-infected subjects. e PR and 95% CI are shown for continuous data. f Data is missing for one infected and two non-infected subjects. g Reported exposure to mud, refuse, flooding water or sewage water in the workplace. h Occupation as construction worker, refuse collector or mechanic, which is associated with a workplace environment characterized by high rat infestation. Panels A and B in Figure 3 show smoothed spatial distributions of subjects with Leptospira antibodies and all subjects, respectively, according to place of residence. The population-adjusted distribution (Figure 3C) showed that risk of acquiring Leptospira antibodies clustered in areas occupied by squatters at the bottom of valleys (Figure 3D). Similar spatial distributions were observed in analyses that used higher titer values to define subjects with Leptospira antibodies (Figure S1). 10.1371/journal.pntd.0000228.g003 Figure 3 Spatial distribution of subjects with Leptospira antibodies and all enrolled subjects, according to place of residence, and environmental attributes of the community site. Panels A and B show the smoothed Kernel density distribution of subjects with Leptospira antibodies (N = 489) and all (N = 3,171) subjects, respectively, according to place of residence. The yellow-to-red gradient represents increasing density in smoothing analyses which used 40 meters as the bandwidth. Black circles show the location of subject households. Panel C shows the distribution of the population-adjusted Kernel density estimator for subjects with Leptospira antibodies which was calculated as the ratio of the estimators for subjects with Leptospira antibodies and all subjects. Panel D shows a topographic map generated by the digital terrain model. The yellow line is the level that is 20 meters above the lowest point in the four valleys within the community site. Panels E and F show the distribution of, respectively, open rainwater and sewage drainage systems and accumulated refuse according to size (m2). Univariate analysis found the risk of acquiring Leptospira antibodies to be associated with increasing age, male gender, indicators of low socioeconomic level, occupations that entail contact with contaminated environments, informal work, time of residence in the study household, and environmental attributes and the presence of reservoirs in the household (Table 1). Significant risk associations were not found for formal employment and reported sighting of rats in the workplace environment. Open rainwater drainage structures and refuse deposits were distributed throughout the site; yet open sewers were more frequently encountered at the bottom of valleys (Figure 3). The distance of household to the nearest open sewer was a risk factor, whereas a significant association was not observed for distance to an open rainwater drainage system. GAM analysis showed that the risk of acquiring Leptospira antibodies had an inverse linear association with the distance of the subject's household to an open sewer and elevation of the household from the lowest point in the valley, a proxy for flood risk (Figure 4). Increased risk was observed among subjects who resided less than a threshold distance of 20 meters to these attributes (Figure 4B and C). The risk of acquiring Leptospira antibodies had an inverse non-linear association with distance of the subject's household to an open refuse deposit (results not shown). We explored a range of dichotomization criteria and found significant risk associations when subjects resided less than 20 meters from an open refuse deposit (Table 1). This association was not influenced by the size of the refuse deposit. Subjects who reported sighting two or more rats in the household environment had increased risk of acquiring Leptospira antibodies (Figure 4D). Household per capita income had an inverse linear association with the presence of Leptospira antibodies (Figure 4A). Of note, the distance of the household to an open sewer was highly correlated (Spearmen correlation coefficient = 0.71) with household elevation (Figure S2A) since open sewers drain into the bottom of valleys. An aggregate variable, distance of household located less than 20 meters from an open sewer and lowest point in a valley, was therefore used to examine the association between open sewer and flood-related exposure and infection risk (Table 1). In contrast household per capita income was not highly correlated (Spearmen correlation coefficient = 0.16) with the elevation of the household (Figure S2B). 10.1371/journal.pntd.0000228.g004 Figure 4 Generalized additive models (GAM) of the association between the risk of acquiring Leptospira antibodies and continuous variables of (A) per capita daily household income, (B) level of household in meters above the lowest point in valley, and (C) distance in meters to the nearest open sewer, and (D) reported number of rats sighted in the household environment. The coefficient, f(infection), in the GAM model is a measure for the risk of acquiring Leptospira antibodies. In Panels A, B, C and D, the x axis intercept values, where f(infection) equals zero, were US$1.70/day, 22 meters, 22 meters and 2 rats, respectively. Multivariate analyses found that the risk for acquiring Leptospira antibodies was associated with exposures in the household environment and not in the workplace setting (Table 1). Subjects who resided less than 20 meters from an open sewer and the lowest point in the valley had a 1.42 times (95% CI 1.14–1.75) increased risk for acquiring Leptospira antibodies than those who lived 20 meters or more from these attributes. Residence less than 20 meters from accumulated refuse was associated with a 1.43 times (95% CI 1.04–1.88) increased risk. Sighting of two or more rats and presence of chickens, a marker for rat infestation, in the household were significant reservoir-associated risk factors. After controlling for age, gender and significant environmental exposures, indicators of low socioeconomic level, household per capita income (PR 0.89 for an increase of US$1.00 per day, 95% CI 0.82–0.95) and black race (PR 1.25, 95% CI 1.03–1.50) were risk factors for acquiring Leptospira antibodies (Table 1). Discussion Efforts to identify interventions for urban leptospirosis have been hampered by the lack of population-based information on transmission determinants. In this large community-based survey of a slum settlement in Brazil, we found that 15% of the residents had serologic evidence for a prior Leptospira infection. The prevalence rate of Leptospira antibodies in the study slum community was similar to that (12%) found in a city-wide survey performed in Salvador [39]. Risk factors for acquiring Leptospira antibodies were associated with exposures in the household environment. Interventions therefore need to target the environmental sources of transmission - open sewers, flooding, open refuse deposits and animal reservoirs - in the places where slum inhabitants reside. After controlling for the influence of poor environment, indicators of low socioeconomic status were found to be independently associated with the risk of acquiring Leptospira antibodies. This finding suggests that in slum communities with overall high levels of absolute poverty, relative differences in socioeconomic level contribute to unequal outcomes for leptospirosis. Leptospirosis has been traditionally considered an occupational disease, since work-related activities are frequently identified as risk exposures [9]. However slum inhabitants reside in close proximity to animal reservoirs and environmental surface waters which contain Leptospira [10]. We previously found that Leptospira infection clusters within households in slum communities in Salvador [40]. In this study, we found that after controlling for confounding, significant risk exposures were those associated with the household environment rather than workplace. As a caveat, interview-elicited responses were used to evaluate work-related exposures since GIS surveys were not performed at the sites where subjects worked. It is possible that slum residents may have had work-related risk exposures which were not detected by our survey. Nevertheless, our findings support the conclusion that the slum household is an important site for Leptospira transmission and provides the rationale for interventions that target risk exposures in this environment. The study's findings indicate that the domestic rat was the principal reservoir for Leptospira transmission in the study community. Highest agglutination titers among 89% of the subjects were directed against L. interrogans serovar Copenhageni, the serovar associated with the R. norvegicus reservoir. Reported sighting of rats is considered to be an unreliable marker of rat infestation. However we found that the number of rats sighted by residents was correlated with their risk of acquiring Leptospira antibodies (Figure 4D), indicating that rat sightings may be a useful marker of infection risk in slum communities where inhabitants are accustomed to the presence of rats. Although dogs were not found to be a risk factor, detailed investigations of Leptospira carriage in urban reservoirs need to be performed. Of note, the presence of chickens in households was a risk factor, although they in of themselves are not reservoirs. This association may reflect a rat-related exposure not accounted for by reported sightings, since rats are attracted to chicken feed and waste. Raising chickens is a widespread practice in slum communities-48% (519) of the 1079 study households raised chickens. Control of rodent reservoir populations may therefore need to incorporate measures that directly address this practice. Our findings confirm hypotheses raised by previous ecologic studies [6],[10],[11] that infrastructure deficiencies related to open sewers, flooding and open refuse deposits are transmission sources for leptospirosis in the slum environment. Furthermore, there appears to be defined areas of risk associated with open sewers and refuse deposits, which serve as habitats and sources of food for rats. Home range radius of the domestic rat varies from 30–150 meters [41],[42], but home range use decreases from the centre to the edge. GAM analysis demonstrated that slum residents had a positive risk for acquiring Leptospira antibodies when households were situated within 20 meters from open sewers and refuse deposits. In addition, infection risk increased as distances from an open sewer or refuse deposit decreased, suggesting that households which are situated closer to these foci have a higher degree of environmental contamination with Leptospira and inhabitants of these households are exposed to higher inoculum doses during infection. Molecular approaches to quantify Leptospira in environmental samples [10] will be useful in answering this question and guiding recommendations for environmental decontamination and barrier control measures which can be implemented in slum communities. In addition, GAM analysis found that residents had positive risk for Leptospira infection when their households were situated within 20 meters from the lowest point in the valley (Figure 4B). In Salvador [6],[12],[16],[40] and other urban centers [11],[13],[15],[17],[18], outbreaks of leptospirosis occur during heavy rainfall and flooding events. Slum communities are built on the poor land quality and often in areas susceptible to frequent flooding. At the study site and other slum settlements in Salvador, the water table rises up to one meter during flooding events because of inadequate rainwater drainage and blockage of drainage systems with silt and refuse. The finding that subjects had increased infection risk when their households were located within 20 meters from the lowest point in the valley suggests that this distance was a proxy for the degree of contact which residents encounter flood-related exposures in the peri-domiciliary environment. We found that in addition to attributes of the environment where slum inhabitants reside, low per capita household income and black race, an indicator of health inequality in Brazil [43],[44], were independent risk factors for Leptospira infection. The social gradient in health is a widespread phenomenon [45],[46]. Our findings, although not unexpected, are noteworthy since they suggest that differences in status contribute to unequal health outcomes in a slum community where the household per capita income was less than US$1 per day for 44% of the inhabitants. Although errors in the measurement of risk exposures and residual confounding were a possibility, the strength of the association indicates a role for social determinants in Leptospira transmission. These factors may relate to risky behaviors, such as cleaning open sewers after flooding events, or limited use of protective clothing which reduce the risk of abrasions that facilitate entry of the Leptospira spirochete [47]. Low status and lack of access to amenities and social support are features of disadvantaged communities [45] which conceivably influence risk behaviors for leptospirosis. Further research is needed to evaluate the role of social factors such that effective interventions, including health education, can be implemented at the community level. A limitation of our study was the cross-sectional design which used serologic evidence for a prior Leptospira infection as the outcome. The MAT is the standard assay used in prevalence surveys [9], yet there is not an established titer criterion for defining seropositive reactions. We previously found that a MAT titer of ≥1∶25 was a specific marker for prior Leptospira infection among slum residents from Salvador and when applied, identified household clustering of infection risk [40]. In this study, cutoff titers from 1∶25 and above identified similar risk associations. In Salvador, leptospirosis is due to transmission of a single agent, L. interrogans serovar Copenhageni [6],[28]. Titers of 1∶25, as well as higher titers, were directed against this serovar (Figure 1), indicating that this cutoff was a specific and more sensitive criteria for identifying prior infections in a region where a single serovar agent is circulating. In the study, there were more men and younger subjects among non-participating subjects than participating subjects. Crude prevalence was not different from the prevalence of Leptospira antibodies which was adjusted by the age and gender distribution of the overall study population, indicating that differences between participating and non-participating subjects may not have introduced a significant bias in the estimates. Infections may have occurred up to five years prior to the survey since agglutinating antibodies may persist for this period [48],[49]. Major interventions to improve basic sanitation were not implemented in the study community, yet the possibility that environmental exposures were modified over time can not be excluded. Migration may have affected our ability to estimate prevalence and risk associations. An on-going cohort investigation of subjects enrolled in this study found that the annual out-migration rate is approximately 12% (unpublished data). The study's findings therefore need to be confirmed in prospective studies. We found that Leptospira transmission was due to the interaction of factors associated with climate, geography and urban poverty. Since the study was performed in a single community in Salvador, Brazil, our findings may not be generalizable to other slum settings. However, a large proportion of the world's slum population resides in tropical climates similar to that in Salvador. Moreover, similar conditions of poverty and environmental degradation encountered at the study site (Figure 1B) are found in many slum settlements. In Brazil, 37% of the urban population resides in slums with equal or greater levels of poverty as found in the study community [33]. Our findings may therefore be relevant to other slum communities where leptospirosis is endemic and have increasing significance as global climate change [26],[27] and growth of the world's slum population occur in the future [1],[33]. The infrastructure deficiencies which were found to be transmission factors for Leptospira in this study can be readily addressed by improving sanitation in slum communities. Investment in sanitation is a cost-effective health intervention [50],[51]. In Salvador, a city-wide sanitation program (Bahia Azul) was recently shown to have a major beneficial impact for diarrheal disease [52]. However, as frequently encountered with large-scale sanitation projects, the Bahia Azul program did not provide coverage to the study community and many of the slum settlements in the city's periphery. Equitable access to improved sanitation is therefore essential in reducing the burden of the large number of environmentally-transmitted infectious diseases, including leptospirosis, which affects slum populations. Furthermore, the finding that the social gradient within slum communities, in addition to the unhealthy environment, contributes to the risk of Leptospira infection suggests that prevention of urban leptospirosis will need to combine approaches for improving sanitation with approaches that identify and address the social determinants which produce unequal health outcomes. Supporting Information Figure S1 Smoothed Kernel density distribution of subjects with microscopic agglutination test titres of ≥1∶25 (A), ≥1∶50 (B) and ≥1∶100 (C), according to place of residence at the study site. The yellow-to-red gradient represents increasing density in smoothing analyses which used 40 meters as the bandwidth. (2.61 MB TIF) Click here for additional data file. Figure S2 Spot plots of the relationship between elevation of household level from the lowest point in valley and distance of the household to the nearest open sewer (A) and household per capita daily income (B). Closed and open dots represent houses with at least one seropositive subject and without a seropositive subject, respectively. (1.02 MB TIF) Click here for additional data file. Alternative Language Abstract S1 Abstract translated into Portuguese by Dr. Guilherme Ribeiro. (0.03 MB DOC) Click here for additional data file.
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              Spatial and Temporal Clustering of Dengue Virus Transmission in Thai Villages

              Introduction Dengue is the leading cause of human arboviral disease worldwide. Dengue viruses (DENV) of the family Flaviviridae and genus Flavivirus, co-circulate as four antigenically related serotypes (DENV-1, −2, −3, and −4), each in varying annual frequencies in Thailand [1] and other tropical countries. The container-breeding mosquito Aedes aegypti (L.) serves as the primary vector responsible for DENV transmission within human populations. Females feed preferentially and frequently on human blood and consequently live in and around human dwellings [2,3]. Transmission of DENV to humans results in either inapparent infection, undifferentiated febrile illness, dengue fever (DF), or life-threatening dengue hemorrhagic fever (DHF). Except for a few notable exceptions, vector control (larvicide treatments, insecticide sprays, and source reduction) has been ineffectively implemented, and no vaccine or clinical cure is yet available for use. Consequently, DENV remain a major cause of morbidity in the tropics and threaten to further expand geographically. DENV transmission and disease are determined by a combination of factors [4] involving the human host [5–7], virus [8–11], mosquito vector [12,13], and environment [13]. Although past studies have revealed general temporal and spatial patterns in the distribution and abundance of Ae. aegypti and human DENV infections [14–18], greater resolution of transmission dynamics across finer geographic and temporal scales is needed to refine current dengue surveillance and control strategies. In an earlier prospective cohort study of schoolchildren in Thailand, Endy and others [19] reported a nonuniform distribution of DENV illness and viral serotypes. To test the hypothesis that DENV transmission is spatially and temporally focal, we extended the school-based study design to include cluster investigations [20] in villages associated with schools. By sampling children and mosquitoes within the neighborhood of children absent from school with fever and dengue viremia, we hypothesized that we would be able to detect, in the same general area and time, other human and mosquito infections and more precisely identify determinants of transmission risk. We used school-based dengue cases to trigger village surveillance of children and mosquitoes within spatial and temporal clusters. We sought a rigorous study of cluster areas over a 15-d period to more accurately define the burden of DENV within a prescribed area (both inapparent and symptomatic infections) and its relationship to mosquito density and infectivity. On the basis of our data, we aimed to consider implications on improving disease prevention strategies. Methods Study Area and Selection of Schools and Villages Our study area (Muang District, Kamphaeng Phet Province [KPP], north-central Thailand [19]) is, by Thai standards, relatively sparsely populated with 233,033 residents in 63,500 houses in an area encompassing 1,962 km2. The average temperature is 28.0 °C with an average monthly rainfall of approximately 200 mm during the rainy months of May to October (National Statistical Office). We selected 11 participating primary schools on the basis of higher numbers of hospitalized dengue cases amongst their students during the prior 5 y, proximity to our field station, and interest of the school administrators. Selected schools (Figure 1) were associated with 32 villages (8,445 houses). Given the workload limitations of entomological surveys, 20 of these villages (4,685 houses) were selected for inclusion on the basis of the density of houses, favoring those with houses in close proximity of each other ( 20–40 m, >40–60 m, >60–80 m, and >80–100 m). In order to evaluate for a distance effect in conjunction with enrollee demographics, a multivariate logistic regression model was formulated. Scientific and Ethical Review and Approval The study protocol and consent forms were approved by the AFRIMS Scientific Review Committee and the ethical review committees of the U.S. Army Surgeon General, Thai MoPH, University of California at Davis, University of Massachusetts Medical School, and San Diego State University. Results Initiation of Cluster Investigations Of the 1,204 febrile children (506 in 2004 and 698 in 2005) who provided blood specimens, 48 (28 in 2004 and 20 in 2005) had detectable DENV viremia. Thirty-four cluster investigations were conducted during the study period (Table 2). Ten clusters (five pairs) in 2004 and two clusters (one pair) in 2005 were spatially and temporally matched. The sex and age distribution of the positive and negative index cases were similar. Children in 58% (seven of 12) of the positive clusters (six in 2004 and one in 2005) attended a single school (school number 2). Table 2 Summary of Cluster Investigations Cluster Enrollees Among the 556 village enrollees (217 in positive and 339 in negative clusters), 27 DENV infections were detected during the 15-d follow-up period. These incident infections occurred exclusively in positive clusters (t-test; p < 0.01; AR = 10.4 per 100; 95% confidence interval [CI] 1–19.8 per 100). This result represented a 4.9% risk among enrollees for experiencing a DENV infection within 15 d of cluster initiation, but a 12.4% risk among enrollees who resided in a positive cluster. Cluster number 4 (Figure 2) contributed disproportionately to this difference. However, all but one positive cluster (cluster number 12) exhibited at least one neighbor with dengue within the 15-d period. There was a statistically significant clustering of DENV cases close to the center of positive clusters when we examined all positive clusters together (Figure 3). Demographics of enrollees between positive and negative clusters were comparable (Table 3). There was no difference in distance between the index cases and respective enrollees in the positive and the negative clusters. Table 3 Comparison of Dengue-Positive and Dengue-Negative Clusters Figure 2 Intense DENV Transmission in Cluster 4 Cluster number 4 illustrates extensive DENV transmission occurring within a 15-d period. In comparison, the paired negative cluster (cluster number 5, not shown) included 22 houses, 21 Ae. aegypti, and 15 contacts with no evidence of DENV transmission within a 15-d period. These index cases were 258 m apart and the cluster investigations were initiated 2 d apart. Figure 3 Clustering of DENV Infections within Positive Clusters This graph shows the relationship of distance between the houses of enrollees and the index case in the positive clusters and the proportion of those enrollees that experienced DENV seroconversion. Error bars represent 95% CIs of the proportions. Numbers in parenthesis indicate the number of positive enrollees and the total number of enrollees in each distance interval. The relationship between distance and the proportion of enrollees that are dengue positive was significant (Fisher's exact test, p < 0.001). A multivariate logistic regression model was estimated to examine the focal nature of transmission while controlling for cluster demographics. Distance between the house of each enrollee and the index case was the measure of focality. An indicator variable was used to account for the evidently excessive transmission in cluster number 4. The model included the age and gender of the enrollees as well as the interaction of these two variables. Resulting coefficient estimates, standard errors, and p-values are given in Table 4. A diagnostic test does not indicate a lack of fit (Hosmer-Lemeshow test, p = 0.23) [30]. A negative and significant parameter estimate indicated that the probability of infection decreased as the distance between enrollees and the index house increased. Modeling results also indicate a gender difference in the effect of age on the probability of infection. The probability that a male enrollee seroconverted decreased with age. This effect was not observed among female enrollees, in whom older enrollees had a higher probability of infection. These trends are apparent in the distribution of infections (Figure S1; Table 5). Table 4 Results of Multivariate Logistic Regression Analysis Table 5 Infections among Enrollees in Positive Clusters by Gender and Age Group Clustering was additionally observed within households as has been previously described [31]. Relative risk of dengue seroconversion among household enrollees of a dengue versus non-dengue case was 2.63 (95% CI 0.96–7.21; Pearson's Chi2 test) with an absolute risk of 6.88 per 100 (95% CI 0–17.29), indicating a strong, but not statistically significant trend towards household risk. Of the 27 DENV infections among village enrollees (Table 6), 14 were inapparent, and 13 were symptomatic. Inapparent infections were more likely with primary (five out of six) than secondary (seven out of 19) DENV infections (p = 0.05; Pearson's Chi2 test). All but one positive cluster (cluster number 6) had concordance of serotypes between the index case and viremic enrollees. (Pearson's Chi2 test used.) Table 6 Clinical Spectrum of Illness among 27 Enrollees with DENV Infections Environmental Determinants of Transmission Among environmental features evaluated ( Table 3), positive clusters were less likely to have piped water than were negative clusters. Though the number of water-holding containers was similar in houses with and without piped water (17.6 ± 8.6 versus 17.8 ± 8.1, t-test, p = 0.28), containers with Ae. aegypti larvae or pupae were significantly less abundant in houses with than without piped water (3.2 ± 3.0 versus 4.4 ± 3.3, t-test, p < 0.001). Use of the larvicide Temephos was higher in the schools than in the villages; 43% and 30% of containers had Temephos in schools in 2004 and 2005, respectively. On average 10% of containers had Temephos in the villages during both study years. Mosquito Collections and Spraying A total of 1,022 adult female Ae. aegypti were collected from within and immediately surrounding homes (Figure 1; Table 2) of which eight (0.8%) were PCR-positive. The average proportion of houses sampled was 0.92 in the positive clusters and 0.93 in the negative clusters (t-test, p = 0.53). Average number of Ae. aegypti pupae/person was significantly higher in positive clusters (Table 3). Although no significant differences were detected, all classical entomological indices (House, Container, and Breteau) and average number of female Ae. aegypti adults/person were higher in positive clusters. The average proportion of houses sprayed was 0.87 in the positive clusters and 0.84 in the negative clusters (t-test, p = 0.39). A total of eight female Ae. aegypti were collected from schools associated with cluster initiation; none were PCR-positive. Discussion Although focal DENV transmission has been noted previously [14,15,32], to our knowledge this is the first study to demonstrate, using control clusters and precise human and entomological data, recent DENV transmission that was focal through space and over a short time span (15 d). DENV-infected hosts (27 enrollees) and vectors (eight Ae. aegypti) were exclusively identified in the 12 dengue-positive clusters, despite a nearly 1:2 ratio of enrollees between positive and negative clusters. Furthermore, we observed significant central clustering of DENV cases within positive clusters. We suspect that focal transmission was associated with recent DENV introductions because of the 217 paired serologic specimens from positive cluster enrollees, only one revealed an elevated but declining immunoglobulin M level, which would be indicative of a recent DENV infection occurring up to 60 d prior to cluster initiation [22]. Consequently, we attributed the observed DENV transmission (enrollees with viremia on day 0 or 15 and/or seroconversion between days 0 and 15) to recent virus introductions. This conclusion is in contrast, however, to data published by Beckett and others [20] who conducted cluster investigations in West Jakarta, Indonesia. They detected 175 recent DENV infections upon enrollment in 53 positive clusters compared to our one in 12 positive clusters, arguing against recent virus introduction. We attribute these contrasting results to study design differences. First, we recruited from schools whereas Beckett recruited from a hospital, potentially after the virus had undergone significant community-based amplification. Second, we preferentially enrolled children as the primary susceptible and amplifying portion of the host population. Beckett additionally enrolled adults. Adults may have exhibited greater background dengue immunity that may have confounded the serologic data. Third, Beckett's study was conducted in an urban area, in contrast to rural villages in our study. Differences in transmission dynamics between these kinds of habitats were likely shaped by the frequency of DENV introductions and diversity in human behaviors. Previous studies have documented hyperendemicity of all four DENV serotypes with an approximate 5% annual risk of acquiring an infection in KPP [19]. In our study, cluster number 4 had a 52% attack rate among enrollees sampled during the 15-d follow-up period. However, after excluding this cluster and its matched negative cluster, the adjusted AR remained high (six per 100). This number represented a 12.4% risk of an enrolled child acquiring a DENV infection within a 15-d period when living within 100 m of a child ill with dengue. Eleven of 12 positive clusters had at least one enrollee with acute dengue in addition to the index case. Given the required intrinsic incubation period, and the finding that all eight virus isolates from mosquitoes matched the serotype recovered from the index case suggest, though not definitively, that except for children from whom virus was recovered on day 15, multiple viremic children within a cluster were infected by one or very few infected mosquitoes. Other evidence within our study to further support village- and not school-based vector sources of DENV infection are that: (1) mosquito populations in schools were extremely low, (2) children seroconverting to dengue within a cluster attended different classrooms within the school, (3) genomic sequences of the envelope (E)-regions of the viruses isolated from children and mosquitoes within the same villages were identical (R.G. Jarman, unpublished data), and (4) housemates of dengue seroconverters had a higher relative risk for DENV infection than those of nondengue seroconverters. The latter observation is consistent with previous reports [14–16]. We suspect that the predominance of DENV transmission in KPP villages reflects, at least in part, routine and effective vector control in schools (insecticide every May and July and Temephos to containers every 3 mo), but not in village homes. Differences in transmission observed between positive and negative clusters could not be attributed to differences in enrollee demographics. Differences in behavioral factors, however, could not be excluded. Within positive clusters, risk of infection decreased with age for males and increased with age for females. This observation merits further investigation with a larger sample and analysis of sex-specific behaviors that might modify risk of infection with advancing age. The only statistically significant determinant among environmental features associated with focal DENV transmission was the greater availability of piped water in negative clusters. Though one may consider a causal relationship (that is, less piped water availability leading to greater need for water storage leading to more containers for larval mosquito development resulting in higher dengue risk), we found no difference in the number of containers between cluster types. Although accurate data on water turn-over are difficult to obtain, the greater number of positive containers in positive than in negative clusters could not be explained by a difference in the frequency of container turn-over rates that we measured. These data could reflect a historical norm or behavior in response to lack of reliability of piped water possibly guided by people's knowledge of dengue preventive measures [33]. The only statistically significant difference among entomological indices was the greater number of Ae. aegypti pupae per person in positive than negative clusters. It is important to note that observed mean pupae per person exceed by an order of magnitude the minimum entomological threshold estimated by Focks and others [34] for a different region of Thailand. This implies that even when pupal densities are relatively high, differences in this measure of entomological risk can be epidemiologically informative. Although adult mosquito population density tended to be higher in positive clusters, differences were not statistically significant, perhaps due to limitations in sampling adult Ae. aegypti with backpack aspirators. Alternatively, mosquito density may be most informative when viewed in concert with herd immunity, and mosquito density alone may be less relevant than the presence of DENV-infected mosquitoes that potentially can transmit virus to multiple individuals [2,3]. Dengue cases in enrollees occurred over a wide range of female Ae. aegypti densities (Figure 4). At densities higher than approximately 1.5 Ae. aegypti females per child, clusters were more likely to be positive than negative. This indicates that DENV transmission was more likely to occur at higher vector densities. Figure 4 Relationship between Vector Density and Dengue Cases Relationship between the number of Ae. aegypti females per child and dengue transmission within 12 positive and 22 negative cluster investigations in 2004 and 2005. Dengue transmission is expressed as the number of positive PCRs on days 0 or 15 of study or of dengue seroconversions between days 0 and 15 per child per cluster. Perifocal spraying is a common approach by health departments to contain/control dengue. However, this practice has been found to be ineffective in aborting DENV transmission [13,35]. Our data suggest that if school-based surveillance can be bolstered by rapid, easy-to-use, and affordable diagnostics, spatially and temporally focused vector control in rural areas such as KPP could be more effectively applied to contain new virus introductions and offset the theoretical risk of longitudinal transmission within and beyond village foci. Although the risk of infection decreased significantly with distance from the center of a cluster, we did not examine people living beyond 100 m of an index case. Our study did not define the spatial dimensions of DENV transmission. Nevertheless, we expect that interventions will need to go beyond a 100 m radius of the home of a DENV-infected child because viremic residents or visitors bitten by an infected mosquito can move virus farther than a flying, infected adult female Ae. aegypti [13,35]. We do not know the longitudinal effects of killing adult mosquitoes on transmission within a community. Koenraadt and others [27] determined in our study area that within 1 wk of spraying insecticide inside homes, approximately 50% of prespraying levels of Ae. aegypti populations were reestablished. Identifying only two of 217 child enrollees with dengue viremia on day 15, both approximately 50 m from the index case within the same positive cluster, indicates that vector control can be locally successful when promptly and properly applied in response to a dengue case. Insecticide applications are most effective when applied inside homes where most Ae. aegypti rest [12] and otherwise avoid contact with insecticides applied outdoors [35–37]. Though our study design was rigorous, our conclusions must be considered in the context of largely logistical limitations: (1) We did not sample all children and mosquitoes within the cluster area. (2) We were unable to characterize the serotype of all DENV infections among village enrollees given restrictions in the frequency of collecting blood from children. (3) We did not collect data on human mobility/behavior that may have influenced the dynamics of transmission within the villages. (4) The possible contribution of adults to DENV transmission was not studied. (5) We did not study the seroprevalence profiles of cluster enrollees. Future studies should focus on positive clusters to more fully characterize the transmission dynamics, the impact of human behavior on transmission patterns, the appropriate spatial scale for disease surveillance/control, and identify more practical and cost-effective approaches to rapid dengue diagnosis. Our cluster methodology provided additional epidemiologic insights. Of note, 14 of the 27 cases of dengue among enrollees were clinically inapparent during this period when DENV-4 was the primary serotype circulating. Most (five of six) primary DENV infections detected in our study were clinically inapparent, similar to observations during a predominantly DENV-2 transmission year in Bangkok [38]. The nearly 1:1 ratio of inapparent to symptomatic secondary DENV infections in our study is also consistent with previous results from KPP [19]. DHF occurred in one (8%) of 12 symptomatic infections and one (4%) of 27 DENV infections confirming that severe dengue represents only a small fraction of the total DENV burden. Future cluster studies can complement these clinical and virologic data by examining correlates of protection that limit transmission, early immunologic events via postinoculation pre-illness specimens and their association with disease severity and sequence variation among viruses through time and space as they circulate between human and mosquito hosts. The prospective cluster methodology utilized here and by others [20] has the potential for broad application. It can be used for multidisciplinary transmission studies of other vector-borne viral diseases as well as spatially and temporally clustered infectious diseases. Supporting Information Figure S1 The Predicted Probability of Infection for Enrollees within Positive Clusters as a Function of Distance to the Index House The probabilities are given for males and females ages 3, 8, and 13 y. Model parameters are reported in Table 5. (51 KB DOC) Click here for additional data file.
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                Author and article information

                Journal
                Science
                Science
                American Association for the Advancement of Science (AAAS)
                0036-8075
                1095-9203
                February 07 2019
                February 08 2019
                February 07 2019
                February 08 2019
                : 363
                : 6427
                : 607-610
                Article
                10.1126/science.aav6618
                © 2019

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