Seroprevalence and Spatial Epidemiology of Lymphatic Filariasis in American Samoa after Successful Mass Drug Administration

Background

As part of the Global Programme to Eliminate Lymphatic Filariasis (LF), American Samoa conducted mass drug administration (MDA) from 2000–2006, and passed transmission assessment surveys in 2011–2012. We examined the seroprevalence and spatial epidemiology of LF post-MDA to inform strategies for ongoing surveillance and to reduce resurgence risk.

Methods

ELISA for LF antigen (Og4C3) and antibodies (Wb123, Bm14) were performed on a geo-referenced serum bank of 807 adults collected in 2010. Risk factors assessed for association with sero-positivity included age, sex, years lived in American Samoa, and occupation. Geographic clustering of serological indicators was investigated to identify spatial dependence and household-level clustering.

Results

Og4C3 antigen of >128 units (positive) were found in 0.75% (95% CI 0.3–1.6%) of participants, and >32 units (equivocal plus positive) in 3.2% (95% CI 0.6–4.7%). Seroprevalence of Wb123 and Bm14 antibodies were 8.1% (95% CI 6.3–10.2%) and 17.9% (95% CI 15.3–20.7%) respectively. Antigen-positive individuals were identified in all ages, and antibody prevalence higher in older ages. Prevalence was higher in males, and inversely associated with years lived in American Samoa. Spatial distribution of individuals varied significantly with positive and equivocal levels of Og4C3 antigen, but not with antibodies. Using Og4C3 cutoff points of >128 units and >32 units, average cluster sizes were 1,242 m and 1,498 m, and geographical proximity of households explained 85% and 62% of the spatial variation respectively.

Conclusions

High-risk populations for LF in American Samoa include adult males and recent migrants. We identified locations and estimated the size of possible residual foci of antigen-positive adults, demonstrating the value of spatial analysis in post-MDA surveillance. Strategies to monitor cluster residents and high-risk groups are needed to reduce resurgence risk. Further research is required to quantify factors contributing to LF transmission at the last stages of elimination to ensure that programme achievements are sustained.     

Detection of Tuberculosis Infection Hotspots Using Activity Spaces Based Spatial Approach in an Urban Tokyo,from 2003 to 2011

Background

Identifying ongoing tuberculosis infection sites is crucial for breaking chains of transmission in tuberculosis-prevalent urban areas. Previous studies have pointed out that detection of local accumulation of tuberculosis patients based on their residential addresses may be limited by a lack of matching between residences and tuberculosis infection sites. This study aimed to identify possible tuberculosis hotspots using TB genotype clustering statuses and a concept of “activity space”, a place where patients spend most of their waking hours. We further compared the spatial distribution by different residential statuses and describe urban environmental features of the detected hotspots.

Methods

Culture-positive tuberculosis patients notified to Shinjuku city from 2003 to 2011 were enrolled in this case-based cross-sectional study, and their demographic and clinical information, TB genotype clustering statuses, and activity space were collected. Spatial statistics (Global Moran’s I and Getis-Ord Gi* statistics) identified significant hotspots in 152 census tracts, and urban environmental features and tuberculosis patients’ characteristics in these hotspots were assessed.

Results

Of the enrolled 643 culture-positive tuberculosis patients, 416 (64.2%) were general inhabitants, 42 (6.5%) were foreign-born people, and 184 were homeless people (28.6%). The percentage of overall genotype clustering was 43.7%. Genotype-clustered general inhabitants and homeless people formed significant hotspots around a major railway station, whereas the non-clustered general inhabitants formed no hotspots. This suggested the detected hotspots of activity spaces may reflect ongoing tuberculosis transmission sites and were characterized by smaller residential floor size and a higher proportion of non-working households.

Conclusions

Activity space-based spatial analysis suggested possible TB transmission sites around the major railway station and it can assist in further comprehension of TB transmission dynamics in an urban setting in Japan.     

A Comparison of Grizzly Bear Demographic Parameters Estimated from Non-Spatial and Spatial Open Population Capture-Recapture Models

Capture-recapture studies are frequently used to monitor the status and trends of wildlife populations. Detection histories from individual animals are used to estimate probability of detection and abundance or density. The accuracy of abundance and density estimates depends on the ability to model factors affecting detection probability. Non-spatial capture-recapture models have recently evolved into spatial capture-recapture models that directly include the effect of distances between an animal’s home range centre and trap locations on detection probability. Most studies comparing non-spatial and spatial capture-recapture biases focussed on single year models and no studies have compared the accuracy of demographic parameter estimates from open population models. We applied open population non-spatial and spatial capture-recapture models to three years of grizzly bear DNA-based data from Banff National Park and simulated data sets. The two models produced similar estimates of grizzly bear apparent survival, per capita recruitment, and population growth rates but the spatial capture-recapture models had better fit. Simulations showed that spatial capture-recapture models produced more accurate parameter estimates with better credible interval coverage than non-spatial capture-recapture models. Non-spatial capture-recapture models produced negatively biased estimates of apparent survival and positively biased estimates of per capita recruitment. The spatial capture-recapture grizzly bear population growth rates and 95% highest posterior density averaged across the three years were 0.925 (0.786–1.071) for females, 0.844 (0.703–0.975) for males, and 0.882 (0.779–0.981) for females and males combined. The non-spatial capture-recapture population growth rates were 0.894 (0.758–1.024) for females, 0.825 (0.700–0.948) for males, and 0.863 (0.771–0.957) for both sexes. The combination of low densities, low reproductive rates, and predominantly negative population growth rates suggest that Banff National Park’s population of grizzly bears requires continued conservation-oriented management actions.     

Spatio-temporal clustering of Mountain-type Zoonotic Visceral Leishmaniasis in China between 2015 and 2019

With several decades of concerted control efforts, visceral leishmaniasis(VL) eradication had almost been achieved in China. However, VL cases continue to be detected in parts of western China recent years. Using data of reported cases, this study aimed to investigate the epidemiology and spatio⁃temporal distribution, of mountain-type zoonotic visceral leishmaniasis (MT-ZVL) in China between the years 2015 and 2019. Epidemiological data pertaining to patients with visceral leishmaniasis (VL) were collected in Gansu, Shaanxi, Sichuan, Shanxi, Henan and Hebei provinces between the years 2015 and 2019. Joinpoint regression analysis was performed to determine changes in the epidemic trend of MT-ZVL within the time period during which data was collected. Spatial autocorrelation of infection was examined using the Global Moran’s I statistic wand hotspot analysis was carried out using the Getis-Ord Gi* statistic. Spatio-temporal clustering analysis was conducted using the retrospective space-time permutation flexible spatial scanning statistics. A total of 529 cases of MT-ZVL were detected in the six provinces from which data were collected during the study time period, predominantly in Gansu (55.0%), Shanxi (21.7%), Shaanxi (12.5%) and Sichuan (8.9%) provinces. A decline in VL incidence in China was observed during the study period, whereas an increase in MT-ZVL incidence was observed in the six provinces from which data was obtained (t = 4.87, P < 0.05), with highest incidence in Shanxi province (t = 16.91, P < 0.05). Significant differences in the Moran’s I statistic were observed during study time period (P < 0.05), indicating spatial autocorrelation in the spatial distribution of MT-ZVL. Hotspot and spatial autocorrelation analysis revealed clustering of infection cases in the Shaanxi-Shanxi border areas and in east of Shanxi province, where transmission increased rapidly over the study duration, as well as in well know high transmission areas in the south of Gansu province and the north of the Sichuan province. It indicates resurgence of MT-ZVL transmission over the latter three years of the study. Spatial clustering of infection was observed in localized areas, as well as sporadic outbreaks of infection.     

Functional correlates of the lateral and medial entorhinal cortex: objects,path integration and local–global reference frames

The hippocampus receives its major cortical input from the medial entorhinal cortex (MEC) and the lateral entorhinal cortex (LEC). It is commonly believed that the MEC provides spatial input to the hippocampus, whereas the LEC provides non-spatial input. We review new data which suggest that this simple dichotomy between ‘where’ versus ‘what’ needs revision. We propose a refinement of this model, which is more complex than the simple spatial–non-spatial dichotomy. MEC is proposed to be involved in path integration computations based on a global frame of reference, primarily using internally generated, self-motion cues and external input about environmental boundaries and scenes; it provides the hippocampus with a coordinate system that underlies the spatial context of an experience. LEC is proposed to process information about individual items and locations based on a local frame of reference, primarily using external sensory input; it provides the hippocampus with information about the content of an experience.     

Knowledge of Lassa fever,its prevention and control practices and their predictors among healthcare workers during an outbreak in Northern Nigeria: A multi-centre cross-sectional assessment

BackgroundThe year 2020 Lassa fever (LF) outbreak had the greatest disease burden and this can place an enormous strain on the already overstretched healthcare system and can potentially increase morbidity and mortality due to infectious diseases.Therefore, having a knowledgeable healthcare workforce with appropriate skills and competencies to prevent and manage outbreaks of a neglected infectious disease such as LF in Nigeria will potentially enhance public health. Thus, this survey assessed the level of knowledge of LF and its prevention and control (PC) measures amongst the healthcare workers (HCWs) during a LF outbreak in Katsina state, Nigeria.Methodology/Principal findingsDuring this cross-sectional survey, HCWs complete a validated 29-item questionnaire comprising 18 items on the knowledge of LF and its PC measures and an item on global self-evaluation of their LF knowledge. Psychometric properties of the questionnaire were evaluated. Chi-square and binary logistic regression analyses were conducted.Out of 435 HCWs invited, a total of 400 participated in the study (92% response rate). The majority of participants (51.8%) demonstrated inadequate LF knowledge, with 62.9% of those scoring low having a high self-perception of their LF knowledge with the global scale. This LF knowledge over-estimation was predicted by LF training status (odds ratio (OR) 2.53; 95% CI: 1.49–4.30; p = 0.001). The level of LF knowledge and its PC measures among the study participants was low (11.60±8.14, 64.4%) and predicted by participants’ LF training status (OR 2.06; 95% CI: 1.19–3.57; p = 0.009), place of work (OR 1.82; 95% CI: 1.07–3.08; p = 0.03) and their designations (OR 2.40; 95% CI: 1.10–5.22; p = 0.03).ConclusionThe level of knowledge of LF and its PC measures among the HCWs surveyed was suboptimal and participants’ LF training status, place of work and occupational category were the significant predictors. In addition, LF knowledge overestimation on a global scale was observed among a majority of HCWs and this was also predicted by LF training status. Therefore, there is a critical need for health authorities in Nigeria to prioritize continuous on-the-job training of HCWs on priority neglected tropical diseases such as Lassa fever.     

Spatio-Temporal Analysis of Smear-Positive Tuberculosis in the Sidama Zone,Southern Ethiopia

Background

Tuberculosis (TB) is a disease of public health concern, with a varying distribution across settings depending on socio-economic status, HIV burden, availability and performance of the health system. Ethiopia is a country with a high burden of TB, with regional variations in TB case notification rates (CNRs). However, TB program reports are often compiled and reported at higher administrative units that do not show the burden at lower units, so there is limited information about the spatial distribution of the disease. We therefore aim to assess the spatial distribution and presence of the spatio-temporal clustering of the disease in different geographic settings over 10 years in the Sidama Zone in southern Ethiopia.

Methods

A retrospective space–time and spatial analysis were carried out at the kebele level (the lowest administrative unit within a district) to identify spatial and space-time clusters of smear-positive pulmonary TB (PTB). Scan statistics, Global Moran’s I, and Getis and Ordi (Gi*) statistics were all used to help analyze the spatial distribution and clusters of the disease across settings.

Results

A total of 22,545 smear-positive PTB cases notified over 10 years were used for spatial analysis. In a purely spatial analysis, we identified the most likely cluster of smear-positive PTB in 192 kebeles in eight districts (RR= 2, p<0.001), with 12,155 observed and 8,668 expected cases. The Gi* statistic also identified the clusters in the same areas, and the spatial clusters showed stability in most areas in each year during the study period. The space-time analysis also detected the most likely cluster in 193 kebeles in the same eight districts (RR= 1.92, p<0.001), with 7,584 observed and 4,738 expected cases in 2003-2012.

Conclusion

The study found variations in CNRs and significant spatio-temporal clusters of smear-positive PTB in the Sidama Zone. The findings can be used to guide TB control programs to devise effective TB control strategies for the geographic areas characterized by the highest CNRs. Further studies are required to understand the factors associated with clustering based on individual level locations and investigation of cases.     

Lymphatic filariasis epidemiology in Samoa in 2018: Geographic clustering and higher antigen prevalence in older age groups

BackgroundSamoa conducted eight nationwide rounds of mass drug administration (MDA) for lymphatic filariasis (LF) between 1999 and 2011, and two targeted rounds in 2015 and 2017 in North West Upolu (NWU), one of three evaluation units (EUs). Transmission Assessment Surveys (TAS) were conducted in 2013 (failed in NWU) and 2017 (all three EUs failed). In 2018, Samoa was the first in the world to distribute nationwide triple-drug MDA using ivermectin, diethylcarbamazine, and albendazole. Surveillance and Monitoring to Eliminate LF and Scabies from Samoa (SaMELFS Samoa) is an operational research program designed to evaluate the effectiveness of triple-drug MDA on LF transmission and scabies prevalence in Samoa, and to compare the usefulness of different indicators of LF transmission. This paper reports results from the 2018 baseline survey and aims to i) investigate antigen (Ag) prevalence and spatial epidemiology, including geographic clustering; ii) compare Ag prevalence between two different age groups (5–9 years versus ≥10 years) as indicators of areas of ongoing transmission; and iii) assess the prevalence of limb lymphedema in those aged ≥15 years.MethodsA community-based cluster survey was conducted in 30 randomly selected and five purposively selected clusters (primary sampling units, PSUs), each comprising one or two villages. Participants were recruited through household surveys (age ≥5 years) and convenience surveys (age 5–9 years). Alere Filariasis Test Strips (FTS) were used to detect Ag, and prevalence was adjusted for survey design and standardized for age and gender. Adjusted Ag prevalence was estimated for each age group (5–9, ≥10, and all ages ≥5 years) for random and purposive PSUs, and by region. Intraclass correlation (ICC) was used to quantify clustering at regions, PSUs, and households.ResultsA total of 3940 persons were included (1942 children aged 5–9 years, 1998 persons aged ≥10 years). Adjusted Ag prevalence in all ages ≥5 years in randomly and purposively selected PSUs were 4.0% (95% CI 2.8–5.6%) and 10.0% (95% CI 7.4–13.4%), respectively. In random PSUs, Ag prevalence was lower in those aged 5–9 years (1.3%, 95% CI 0.8–2.1%) than ≥10 years (4.7%, 95% CI 3.1–7.0%), and poorly correlated at the PSU level (R-square = 0.1459). Adjusted Ag prevalence in PSUs ranged from 0% to 10.3% (95% CI 5.9–17.6%) in randomly selected and 3.8% (95% CI 1.3–10.8%) to 20.0% (95% CI 15.3–25.8%) in purposively selected PSUs. ICC for Ag-positive individuals was higher at households (0.46) compared to PSUs (0.18) and regions (0.01).ConclusionsOur study confirmed ongoing transmission of LF in Samoa, in accordance with the 2017 TAS results. Ag prevalence varied significantly between PSUs, and there was poor correlation between prevalence in 5–9 year-olds and older ages, who had threefold higher prevalence. Sampling older age groups would provide more accurate estimates of overall prevalence, and be more sensitive for identifying residual hotspots. Higher prevalence in purposively selected PSUs shows local knowledge can help identify at least some hotspots.     

Maximizing surveillance through spatial characterization of marine mammal stranding hot spots

Spatial analyses of marine mammal stranding data can be used to identify stranding patterns and improve surveillance and monitoring. Using ArcGIS and SaTScan, we analyzed 12 years (2002–2014) of dead beachcast marine mammals from San Juan County, Washington, to better understand patterns of carcass deposition. We plotted the locations for 631 dead marine mammals and aggregated strandings into 1,000 m segments of shoreline. “Hot spots” included beach segments with significantly higher carcass deposition according to the Getis-Ord Gi* statistic in ArcGIS or beach segments that were encompassed by significant spatial clusters using the discrete Poisson model in SatTScan. We identified 52 hot spots for harbor seals (Phoca vitulina) in ArcGIS and 62 hot spots in SaTScan with 81% agreement between methods. Carcass deposition showed a strong relationship with locations having high proximity to public pedestrian access points, suggesting increased reporting effort in those areas. Stranding frequency was also higher on beach segments with longer fetch and nearly level or gentle slopes. Beaches with these geomorphic characteristics, especially those without high proximity to public access, would be ideal locations to actively survey to improve high quality carcass collection during times of high expected mortality and limited resources.     

Achievements and challenges of lymphatic filariasis elimination in Sierra Leone

BackgroundLymphatic filariasis (LF) is targeted for elimination in Sierra Leone. Epidemiological coverage of mass drug administration (MDA) with ivermectin and albendazole had been reported >65% in all 12 districts annually. Eight districts qualified to implement transmission assessment survey (TAS) in 2013 but were deferred until 2017 due to the Ebola outbreak (2014–2016). In 2017, four districts qualified for conducting a repeat pre-TAS after completing three more rounds of MDA and the final two districts were also eligible to implement a pre-TAS.Methodology/Principal findingsFor TAS, eight districts were surveyed as four evaluation units (EU). A school-based survey was conducted in children aged 6–7 years from 30 clusters per EU. For pre-TAS, one sentinel and one spot check site per district (with 2 spot check sites in Bombali) were selected and 300–350 persons aged 5 years and above were selected. For both surveys, finger prick blood samples were tested using the Filariasis Test Strips (FTS).For TAS, 7,143 children aged 6–7 years were surveyed across four EUs, and positives were found in three EUs, all below the critical cut-off value for each EU. For the repeat pre-TAS/pre-TAS, 3,994 persons over five years of age were surveyed. The Western Area Urban had FTS prevalence of 0.7% in two sites and qualified for TAS, while other five districts had sites with antigenemia prevalence >2%: 9.1–25.9% in Bombali, 7.5–19.4% in Koinadugu, 6.1–2.9% in Kailahun, 1.3–2.3% in Kenema and 1.7% - 3.7% in Western Area Rural.Conclusions/SignificanceEight districts in Sierra Leone have successfully passed TAS1 and stopped MDA, with one more district qualified for conducting TAS1, a significant progress towards LF elimination. However, great challenges exist in eliminating LF from the whole country with repeated failure of pre-TAS in border districts. Effort needs to be intensified to achieve LF elimination.     

Socio-Demographic Predictors and Distribution of Pulmonary Tuberculosis (TB) in Xinjiang,China: A Spatial Analysis

Objectives

Xinjiang is one of the high TB burden provinces of China. A spatial analysis was conducted using geographical information system (GIS) technology to improve the understanding of geographic variation of the pulmonary TB occurrence in Xinjiang, its predictors, and to search for targeted interventions.

Methods

Numbers of reported pulmonary TB cases were collected at county/district level from TB surveillance system database. Population data were extracted from Xinjiang Statistical Yearbook (2006~2014). Spatial autocorrelation (or dependency) was assessed using global Moran’s I statistic. Anselin’s local Moran’s I and local Getis-Ord statistics were used to detect local spatial clusters. Ordinary least squares (OLS) regression, spatial lag model (SLM) and geographically-weighted regression (GWR) models were used to explore the socio-demographic predictors of pulmonary TB incidence from global and local perspectives. SPSS17.0, ArcGIS10.2.2, and GeoDA software were used for data analysis.

Results

Incidence of sputum smear positive (SS+) TB and new SS+TB showed a declining trend from 2005 to 2013. Pulmonary TB incidence showed a declining trend from 2005 to 2010 and a rising trend since 2011 mainly caused by the rising trend of sputum smear negative (SS-) TB incidence (p<0.0001). Spatial autocorrelation analysis showed the presence of positive spatial autocorrelation for pulmonary TB incidence, SS+TB incidence and SS-TB incidence from 2005 to 2013 (P <0.0001). The Anselin’s Local Moran’s I identified the “hotspots” which were consistently located in the southwest regions composed of 20 to 28 districts, and the “coldspots” which were consistently located in the north central regions consisting of 21 to 27 districts. Analysis with the Getis-Ord Gi* statistic expanded the scope of “hotspots” and “coldspots” with different intensity; 30 county/districts clustered as “hotspots”, while 47 county/districts clustered as “coldspots”. OLS regression model included the “proportion of minorities” and the “per capita GDP” as explanatory variables that explained 64% the variation in pulmonary TB incidence (adjR² = 0.64). The SLM model improved the fit of the OLS model with a decrease in AIC value from 883 to 864, suggesting “proportion of minorities” to be the only statistically significant predictor. GWR model also improved the fitness of regression (adj R² = 0.68, AIC = 871), which revealed that “proportion of minorities” was a strong predictor in the south central regions while “per capita GDP” was a strong predictor for the southwest regions.

Conclusion

The SS+TB incidence of Xinjiang had a decreasing trend during 2005–2013, but it still remained higher than the national average in China. Spatial analysis showed significant spatial autocorrelation in pulmonary TB incidence. Cluster analysis detected two clusters—the “hotspots”, which were consistently located in the southwest regions, and the “coldspots”, which were consistently located in the north central regions. The exploration of socio-demographic predictors identified the “proportion of minorities” and the “per capita GDP” as predictors and may help to guide TB control programs and targeting intervention.     

Antibody to the Filarial Antigen Wb123 Reflects Reduced Transmission and Decreased Exposure in Children Born following Single Mass Drug Administration (MDA)

Background

Antibody (Ab) to the Wuchereria bancrofti (Wb) infective larval (L3) antigen Wb123, using a Luciferase Immunoprecipitation System (LIPS) assay, has been shown to be a species-specific, early marker of infection developed for potential use as a surveillance tool following transmission interruption post mass drug administration. To examine its usefulness in a single filarial-endemic island assessed at two time points with markedly different levels of transmission, Ab to Wb123 was measured in sera collected from subjects from Mauke, Cook Islands in 1975 (no previous treatment) and 1992 (5 years after a one time island-wide treatment with diethylcarbamazine [DEC]).

Findings

Between 1975 and 1992, Wb transmission decreased dramatically as evidenced by reduced prevalences of microfilariae (31% vs. 5%) and circulating Ag (CAg, 49% vs. 16%). Age specific prevalence analysis showed a dramatic reduction in Wb123 Ab positivity from 54% (25/46) in 1975 to 8% (3/38) in 1992 in children 1–5 years (p<0.0001), reflecting the effects of single-dose treatment five years earlier. By 1992, Wb123 Ab prevalence in children 6–10 years had fallen from 75% (42/56) in 1975 to 42% (33/79) consistent with a lower cumulative transmission potential. In the whole population, Wb123 seropositivity decreased from 86% to 60% between 1975 and 1992. In CAg+ subjects the levels of Wb123 Ab were indistinguishable between the 2 time points but differed in those who were CAg− (p<0.0001). In paired sample analysis, individuals who were CAg+ in 1975 but became CAg− in 1992 had significantly lower Ab levels in 1992 (p<0.0001), with 9/40 (23%) becoming seronegative for Wb123.

Conclusions

The relationship between reduction in Wb123 Ab prevalence and the reduction of transmission, seen most clearly in young children, strongly advocates for the continuing assessment and rapid development of Wb123 as a surveillance tool to detect potential transmission of bancroftian filariasis in treated endemic areas.     

煤炭开发对矿区植被扰动时空效应的图谱分析——以大同矿区为例

摘要：植被是综合体现矿区生态环境状况的关键因子。以NDVI值为参数,基于像元二分的遥感估算方法测度了1999-2010年大同矿区的植被覆盖情况。利用Global Moran's I、Getis-Ord General G、Getis-Ord Gi*、Anselin Local Moran I等空间关联指数分别从全局演变和局部效应的视角揭示了矿区植被受煤炭开发等活动扰动的时空演化和内在作用机制。研究结果表明：（1）大同矿区植被盖度变化在空间上呈集聚分布状态,表现出很强的空间自相关性,这一现象在植被盖度最低时期最明显;（2）在植被盖度上升期,其变化的热点区不断减少或向次热点地区分散,矿区植被变化集聚效应越发不显著,总体上呈离散的态势。（3）煤炭开发对矿区植被的扰动呈现整体性特征,与煤炭产量成正比。（4）不同植被类型受煤炭开发扰动呈现不同的变化特征。（5）采用循环工艺的高效高产矿井大规模煤炭开发对植被的扰动作用尚不明显,但长期效应有待进一步研究。     

Movement can mediate temporal mismatches between resource availability and biological events in host–pathogen interactions

Global change is shifting the timing of biological events, leading to temporal mismatches between biological events and resource availability. These temporal mismatches can threaten species’ populations. Importantly, temporal mismatches not only exert strong pressures on the population dynamics of the focal species, but can also lead to substantial changes in pairwise species interactions such as host–pathogen systems. We adapted an established individual‐based model of host–pathogen dynamics. The model describes a viral agent in a social host, while accounting for the host''s explicit movement decisions. We aimed to investigate how temporal mismatches between seasonal resource availability and host life‐history events affect host–pathogen coexistence, that is, disease persistence. Seasonal resource fluctuations only increased coexistence probability when in synchrony with the hosts’ biological events. However, a temporal mismatch reduced host–pathogen coexistence, but only marginally. In tandem with an increasing temporal mismatch, our model showed a shift in the spatial distribution of infected hosts. It shifted from an even distribution under synchronous conditions toward the formation of disease hotspots, when host life history and resource availability mismatched completely. The spatial restriction of infected hosts to small hotspots in the landscape initially suggested a lower coexistence probability due to the critical loss of susceptible host individuals within those hotspots. However, the surrounding landscape facilitated demographic rescue through habitat‐dependent movement. Our work demonstrates that the negative effects of temporal mismatches between host resource availability and host life history on host–pathogen coexistence can be reduced through the formation of temporary disease hotspots and host movement decisions, with implications for disease management under disturbances and global change.     

Evaluating spatiotemporal dynamics of snakebite in Sri Lanka: Monthly incidence mapping from a national representative survey sample

BackgroundSnakebite incidence shows both spatial and temporal variation. However, no study has evaluated spatiotemporal patterns of snakebites across a country or region in detail. We used a nationally representative population sample to evaluate spatiotemporal patterns of snakebite in Sri Lanka.MethodologyWe conducted a community-based cross-sectional survey representing all nine provinces of Sri Lanka. We interviewed 165 665 people (0.8% of the national population), and snakebite events reported by the respondents were recorded. Sri Lanka is an agricultural country; its central, southern and western parts receive rain mainly from Southwest monsoon (May to September) and northern and eastern parts receive rain mainly from Northeast monsoon (November to February). We developed spatiotemporal models using multivariate Poisson process modelling to explain monthly snakebite and envenoming incidences in the country. These models were developed at the provincial level to explain local spatiotemporal patterns.Principal findingsSnakebites and envenomings showed clear spatiotemporal patterns. Snakebite hotspots were found in North-Central, North-West, South-West and Eastern Sri Lanka. They exhibited biannual seasonal patterns except in South-Western inlands, which showed triannual seasonality. Envenoming hotspots were confined to North-Central, East and South-West parts of the country. Hotspots in North-Central regions showed triannual seasonal patterns and South-West regions had annual patterns. Hotspots remained persistent throughout the year in Eastern regions. The overall monthly snakebite and envenoming incidences in Sri Lanka were 39 (95%CI: 38–40) and 19 (95%CI: 13–30) per 100 000, respectively, translating into 110 000 (95%CI: 107 500–112 500) snakebites and 45 000 (95%CI: 32 000–73 000) envenomings in a calendar year.Conclusions/significanceThis study provides information on community-based monthly incidence of snakebites and envenomings over the whole country. Thus, it provides useful insights into healthcare decision-making, such as, prioritizing locations to establish specialized centres for snakebite management and allocating resources based on risk assessments which take into account both location and season.     

Scent Lure Effect on Camera-Trap Based Leopard Density Estimates

Density estimates for large carnivores derived from camera surveys often have wide confidence intervals due to low detection rates. Such estimates are of limited value to authorities, which require precise population estimates to inform conservation strategies. Using lures can potentially increase detection, improving the precision of estimates. However, by altering the spatio-temporal patterning of individuals across the camera array, lures may violate closure, a fundamental assumption of capture-recapture. Here, we test the effect of scent lures on the precision and veracity of density estimates derived from camera-trap surveys of a protected African leopard population. We undertook two surveys (a ‘control’ and ‘treatment’ survey) on Phinda Game Reserve, South Africa. Survey design remained consistent except a scent lure was applied at camera-trap stations during the treatment survey. Lures did not affect the maximum movement distances (p = 0.96) or temporal activity of female (p = 0.12) or male leopards (p = 0.79), and the assumption of geographic closure was met for both surveys (p >0.05). The numbers of photographic captures were also similar for control and treatment surveys (p = 0.90). Accordingly, density estimates were comparable between surveys (although estimates derived using non-spatial methods (7.28–9.28 leopards/100km²) were considerably higher than estimates from spatially-explicit methods (3.40–3.65 leopards/100km²). The precision of estimates from the control and treatment surveys, were also comparable and this applied to both non-spatial and spatial methods of estimation. Our findings suggest that at least in the context of leopard research in productive habitats, the use of lures is not warranted.     

Identification of Wb123 as an Early and Specific Marker of Wuchereria bancrofti Infection

Background

The current antibody tests used for monitoring in lymphatic filariasis (LF) elimination programs suffer from poor specificity because of the considerable geographical overlap with other filarial infections such as Loa loa (Ll), Onchocerca volvulus (Ov), and Mansonella perstans (Mp).

Methods

Using bioinformatics to assemble into contigs 2048 expressed sequence tags (ESTs) from the L3 infective larvae of W. bancrofti (Wb), these were next assessed for homology to known proteins and nucleotides and to similar assemblies of L3 larval ESTs of B. malayi (Bm – n = 5068), Ov (n = 4166), and Ll (n = 3315). Nineteen potential L3- and Wb- and/or Bm-specific antigens were identified. Sixteen of the 19 antigens could be expressed as fusion proteins with Renilla luciferase (Ruc); these were used in a rapid Luciferase Immunopreciptation System (LIPS) assay.

Results

One of the 16 expressed antigens (Wb123) was both highly immunogenic and specific for Wb. Using Wb123-based IgG and IgG4 LIPS assays on well-defined sera from normal North Americans and those infected exclusively with intestinal helminths, we could detect all of the Wb-infected individuals (from diverse geographic regions) with 100% sensitivity and 100% specificity. Using sera from exclusively Ll-infected, Ov-infected Mp-infected or Bm-infected subjects as the negative comparator, the sensitivities were between 98–100% and the specificities ranged between 84–100% (for IgG anti-Wb123) and between 98–100% (for IgG4 anti-Wb123). Blinded assessments using panels of sera from various Wb-, Bm- or non-Wb helminth-infected subjects demonstrated equally high degrees of sensitivity and specificity.

Significance

We have identified a Wb-encoded antigen that can be used both as a rapid, high throughput tool to diagnose individual Wb infections and as a sensitive method for early detection of recrudescent infections in areas of control and for mapping new areas of Wb transmission.     

High Rates of O’Nyong Nyong and Chikungunya Virus Transmission in Coastal Kenya

BackgroundChikungunya virus (CHIKV) and o’nyong nyong virus (ONNV) are mosquito-borne alphaviruses endemic in East Africa that cause acute febrile illness and arthritis. The objectives of this study were to measure the seroprevalence of CHIKV and ONNV in coastal Kenya and link it to demographics and other risk factors.MethodologyDemographic and exposure questionnaires were administered to 1,848 participants recruited from two village clusters (Milalani-Nganja and Vuga) in 2009. Sera were tested for alphavirus exposure using standardized CHIKV IgG ELISA protocols and confirmed with plaque reduction neutralization tests (PRNT). Logistic regression models were used to determine the variables associated with seropositivity. Weighted K test for global clustering of houses with alphavirus positive participants was performed for distance ranges of 50–1,000 meters, and G* statistic and kernel density mapping were used to identify locations of higher seroprevalence.Conclusions/SignificanceAlphavirus exposure, particularly ONNV exposure, is common in coastal Kenya with ongoing interepidemic transmission of both ONNV and CHIKV. Women and adults were more likely to be seropositive. Household location may be a defining factor for the ecology of alphaviral transmission in this region.     

Spatial Clustering of All-Cause and HIV-Related Mortality in a Rural South African Population (2000–2006)

Background

Sub-Saharan Africa bears a disproportionate burden of HIV infection. Knowledge of the spatial distribution of HIV outcomes is vital so that appropriate public health interventions can be directed at locations most in need. In this regard, spatial clustering analysis of HIV-related mortality events has not been performed in a rural sub-Saharan African setting.

Methodology and Results

Kulldorff’s spatial scan statistic was used to identify HIV-related and all-cause mortality clusters (p<0.05) in a population-based demographic surveillance survey in rural KwaZulu Natal, South Africa (2000–2006). The analysis was split pre (2000–2003) and post (2004–2006) rollout of antiretroviral therapy, respectively. Between 2000–2006 a total of 86,175 resident individuals ≥15 years of age were under surveillance and 5,875 deaths were recorded (of which 2,938 were HIV-related) over 343,060 person-years of observation (crude all-cause mortality rate 17.1/1000). During both time periods a cluster of high HIV-related (RR = 1.46/1.51, p = 0.001) and high all-cause mortality (RR = 1.35/1.38, p = 0.001) was identified in peri-urban communities near the National Road. A consistent low-risk cluster was detected in the urban township in both time periods (RR = 0.60/0.39, p = 0.003/0.005) and in the first time period (2000–2003) a large cluster of low HIV-related and all-cause mortality in a remote rural area was identified.

Conclusions

HIV-related and all-cause mortality exhibit strong spatial clustering tendencies in this population. Highest HIV-related mortality and all-cause mortality occurred in the peri-urban communities along the National Road and was lowest in the urban township and remote rural communities. The geography of HIV-related mortality corresponded closely to the geography of HIV prevalence, with the notable exception of the urban township where high HIV-related mortality would have been expected on the basis of the high HIV prevalence. Our results suggest that HIV treatment and care programmes should be strengthened in easy-to-reach high density, peri-urban populations near National Roads where both HIV-related and all-cause mortality are highest.     

Stable and Unstable Malaria Hotspots in Longitudinal Cohort Studies in Kenya

Background

Infectious diseases often demonstrate heterogeneity of transmission among host populations. This heterogeneity reduces the efficacy of control strategies, but also implies that focusing control strategies on “hotspots” of transmission could be highly effective.

Methods and Findings

In order to identify hotspots of malaria transmission, we analysed longitudinal data on febrile malaria episodes, asymptomatic parasitaemia, and antibody titres over 12 y from 256 homesteads in three study areas in Kilifi District on the Kenyan coast. We examined heterogeneity by homestead, and identified groups of homesteads that formed hotspots using a spatial scan statistic. Two types of statistically significant hotspots were detected; stable hotspots of asymptomatic parasitaemia and unstable hotspots of febrile malaria. The stable hotspots were associated with higher average AMA-1 antibody titres than the unstable clusters (optical density [OD] = 1.24, 95% confidence interval [CI] 1.02–1.47 versus OD = 1.1, 95% CI 0.88–1.33) and lower mean ages of febrile malaria episodes (5.8 y, 95% CI 5.6–6.0 versus 5.91 y, 95% CI 5.7–6.1). A falling gradient of febrile malaria incidence was identified in the penumbrae of both hotspots. Hotspots were associated with AMA-1 titres, but not seroconversion rates. In order to target control measures, homesteads at risk of febrile malaria could be predicted by identifying the 20% of homesteads that experienced an episode of febrile malaria during one month in the dry season. That 20% subsequently experienced 65% of all febrile malaria episodes during the following year. A definition based on remote sensing data was 81% sensitive and 63% specific for the stable hotspots of asymptomatic malaria.

Conclusions

Hotspots of asymptomatic parasitaemia are stable over time, but hotspots of febrile malaria are unstable. This finding may be because immunity offsets the high rate of febrile malaria that might otherwise result in stable hotspots, whereas unstable hotspots necessarily affect a population with less prior exposure to malaria. Please see later in the article for the Editors'' Summary