Use of remote sensing to identify spatial risk factors for malaria in a region of declining transmission: a cross-sectional and longitudinal community survey

Geospatial based model for malaria risk prediction in Kilombero valley, South-eastern, Tanzania

BACKGROUND

Malaria continues to pose a major public health challenge in tropical regions. Despite significant efforts to control malaria in Tanzania, there are still residual transmission cases. Unfortunately, little is known about where these residual malaria transmission cases occur and how they spread. In Tanzania for example, the transmission is heterogeneously distributed. In order to effectively control and prevent the spread of malaria, it is essential to understand the spatial distribution and transmission patterns of the disease. This study seeks to predict areas that are at high risk of malaria transmission so that intervention measures can be developed to accelerate malaria elimination efforts.

METHODS

This study employs a geospatial based model to predict and map out malaria risk area in Kilombero Valley. Environmental factors related to malaria transmission were considered and assigned valuable weights in the Analytic Hierarchy Process (AHP), an online system using a pairwise comparison technique. The malaria hazard map was generated by a weighted overlay of the altitude, slope, curvature, aspect, rainfall distribution, and distance to streams in Geographic Information Systems (GIS). Finally, the risk map was created by overlaying components of malaria risk including hazards, elements at risk, and vulnerability.

RESULTS

The study demonstrates that the majority of the study area falls under moderate risk level (61%), followed by the low risk level (31%), while the high malaria risk area covers a small area, which occupies only 8% of the total area.

CONCLUSION

The findings of this study are crucial for developing spatially targeted interventions against malaria transmission in residual transmission settings. Predicted areas prone to malaria risk provide information that will inform decision-makers and policymakers for proper planning, monitoring, and deployment of interventions.

Comparing field-collected versus remotely-sensed variables to model malaria risk in the highlands of western Uganda

BACKGROUND

Malaria risk is not uniform across relatively small geographic areas, such as within a village. This heterogeneity in risk is associated with factors including demographic characteristics, individual behaviours, home construction, and environmental conditions, the importance of which varies by setting, making prediction difficult. This study attempted to compare the ability of statistical models to predict malaria risk at the household level using either (i) free easily-obtained remotely-sensed data or (ii) results from a resource-intensive household survey.

METHODS

The results of a household malaria survey conducted in 3 villages in western Uganda were combined with remotely-sensed environmental data to develop predictive models of two outcomes of interest (1) a positive ultrasensitive rapid diagnostic test (uRDT) and (2) inpatient admission for malaria within the last year. Generalized additive models were fit to each result using factors from the remotely-sensed data, the household survey, or a combination of both. Using a cross-validation approach, each model's ability to predict malaria risk for out-of-sample households (OOS) and villages (OOV) was evaluated.

RESULTS

Models fit using only environmental variables provided a better fit and higher OOS predictive power for uRDT result (AIC = 362, AUC = 0.736) and inpatient admission (AIC = 623, AUC = 0.672) compared to models using household variables (uRDT AIC = 376, Admission AIC = 644, uRDT AUC = 0.667, Admission AUC = 0.653). Combining the datasets did not result in a better fit or higher OOS predictive power for uRDT results (AIC = 367, AUC = 0.671), but did for inpatient admission (AIC = 615, AUC = 0.683). Household factors performed best when predicting OOV uRDT results (AUC = 0.596) and inpatient admission (AUC = 0.553), but not much better than a random classifier.

CONCLUSIONS

These results suggest that residual malaria risk is driven more by the external environment than home construction within the study area, possibly due to transmission regularly occurring outside of the home. Additionally, they suggest that when predicting malaria risk the benefit may not outweigh the high costs of attaining detailed information on household predictors. Instead, using remotely-sensed data provides an equally effective, cost-efficient alternative.

What Heterogeneities in Individual-level Mobility Are Lost During Aggregation? Leveraging GPS Logger Data to Understand Fine-scale and Aggregated Patterns of Mobility

Human movement drives spatial transmission patterns of infectious diseases. Population-level mobility patterns are often quantified using aggregated data sets, such as census migration surveys or mobile phone data. These data are often unable to quantify individual-level travel patterns and lack the information needed to discern how mobility varies by demographic groups. Individual-level datasets can capture additional, more precise, aspects of mobility that may impact disease risk or transmission patterns and determine how mobility differs across cohorts; however, these data are rare, particularly in locations such as sub-Saharan Africa. Using detailed GPS logger data collected from three sites in southern Africa, we explore metrics of mobility such as percent time spent outside home, number of locations visited, distance of locations, and time spent at locations to determine whether they vary by demographic, geographic, or temporal factors. We further create a composite mobility score to identify how well aggregated summary measures would capture the full extent of mobility patterns. Although sites had significant differences in all mobility metrics, no site had the highest mobility for every metric, a distinction that was not captured by the composite mobility score. Further, the effects of sex, age, and season on mobility were all dependent on site. No factor significantly influenced the number of trips to locations, a common way to aggregate datasets. When collecting and analyzing human mobility data, it is difficult to account for all the nuances; however, these analyses can help determine which metrics are most helpful and what underlying differences may be present.

Scientific Findings of the Southern and Central Africa International Center of Excellence for Malaria Research: Ten Years of Malaria Control Impact Assessments in Hypo-, Meso-, and Holoendemic Transmission Zones in Zambia and Zimbabwe

For a decade, the Southern and Central Africa International Center of Excellence for Malaria Research has operated with local partners across study sites in Zambia and Zimbabwe that range from hypo- to holoendemic and vary ecologically and entomologically. The burden of malaria and the impact of control measures were assessed in longitudinal cohorts, cross-sectional surveys, passive and reactive case detection, and other observational designs that incorporated multidisciplinary scientific approaches: classical epidemiology, geospatial science, serosurveillance, parasite and mosquito genetics, and vector bionomics. Findings to date have helped elaborate the patterns and possible causes of sustained low-to-moderate transmission in southern Zambia and eastern Zimbabwe and recalcitrant high transmission and fatality in northern Zambia. Cryptic and novel mosquito vectors, asymptomatic parasite reservoirs in older children, residual parasitemia and gametocytemia after treatment, indoor residual spraying timed dyssynchronously to vector abundance, and stockouts of essential malaria commodities, all in the context of intractable rural poverty, appear to explain the persistent malaria burden despite current interventions. Ongoing studies of high-resolution transmission chains, parasite population structures, long-term malaria periodicity, and molecular entomology are further helping to lay new avenues for malaria control in southern and central Africa and similar settings.

Understudied Anophelines Contribute to Malaria Transmission in a Low-Transmission Setting in the Choma District, Southern Province, Zambia

Malaria transmission has declined substantially in Southern Province, Zambia, which is considered a low-transmission setting. The Zambian government introduced a reactive test-and-treat strategy to identify active zones of transmission and treat parasitemic residents. This study was conducted in the Choma District, Southern Province, Zambia, concurrently with an evaluation of this strategy to identify vectors responsible for sustaining transmission, and to identify entomological, spatial, and ecological risk factors associated with increased densities of mosquitoes. Anophelines were collected with CDC light traps indoors and near animal pens in index cases and neighboring households. Outdoor collections captured significantly more anophelines than indoor traps, and 10 different anopheline species were identified. Four species (Anopheles arabiensis, An. rufipes, An. squamosus, and An. coustani) were positive for Plasmodium falciparum circumsporozoite protein by ELISA, and 61% of these 26 anophelines were captured outdoors. Bloodmeal assays confirm plasticity in An. arabiensis foraging, feeding both on humans and animals, whereas An. rufipes, An. squamosus, and An. coustani were largely zoophilic and exophilic. Linear regression of count data for indoor traps revealed that households with at least one parasitemic resident by polymerase chain reaction testing was associated with higher female anopheline counts. This suggests that targeting households with parasitemic individuals for vector interventions may reduce indoor anopheline populations. However, many vectors species responsible for transmission may not be affected by indoor interventions because they are primarily exophilic and forage opportunistically. These data underscore the necessity for further evaluation of vector surveillance and control tools that are effective outdoors, in conjunction with current indoor-based interventions.

Citizen science for monitoring the spatial and temporal dynamics of malaria vectors in relation to environmental risk factors in Ruhuha, Rwanda

Background

As part of malaria prevention and control efforts, the distribution and density of malaria mosquitoes requires continuous monitoring. Resources for long-term surveillance of malaria vectors, however, are often limited. The aim of the research was to evaluate the value of citizen science in providing insight into potential malaria vector hotspots and other malaria relevant information, and to determine predictors of malaria vector abundance in a region where routine mosquito monitoring has not been established to support vector surveillance.

Methods

A 1-year citizen science programme for malaria mosquito surveillance was implemented in five villages of the Ruhuha sector in Bugesera district, Rwanda. In total, 112 volunteer citizens were enrolled and reported monthly data on mosquitoes collected in their peridomestic environment using handmade carbon-dioxide baited traps. Additionally, they reported mosquito nuisance experienced as well as the number of confirmed malaria cases in their household.

Results

In total, 3793 female mosquitoes were collected, of which 10.8% were anophelines. For the entire period, 16% of the volunteers reported having at least one confirmed malaria case per month, but this varied by village and month. During the study year 66% of the households reported at least one malaria case. From a sector perspective, a higher mosquito and malaria vector abundance was observed in the two villages in the south of the study area. The findings revealed significant positive correlations among nuisance reported and confirmed malaria cases, and also between total number of Culicidae and confirmed malaria cases, but not between the numbers of the malaria vector Anopheles gambiae and malaria cases. At the sector level, of thirteen geographical risk factors considered for inclusion in multiple regression, distance to the river network and elevation played a role in explaining mosquito and malaria mosquito abundance.

Conclusions

The study demonstrates that a citizen science approach can contribute to mosquito monitoring, and can help to identify areas that, in view of limited resources for control, are at higher risk of malaria.

Phylogenetic Complexity of Morphologically Identified Anopheles squamosus in Southern Zambia

Despite dramatic reductions in malaria cases in the catchment area of Macha Hospital, Choma District, Southern Province in Zambia, prevalence has remained near 1-2% by RDT for the past several years. To investigate residual malaria transmission in the area, this study focuses on the relative abundance, foraging behavior, and phylogenetic relationships of Anopheles squamosus specimens. In 2011, higher than expected rates of anthropophily were observed among "zoophilic" An. squamosus, a species that had sporadically been found to contain Plasmodium falciparum sporozoites. The importance of An. squamosus in the region was reaffirmed in 2016 when P. falciparum sporozoites were detected in numerous An. squamosus specimens. This study analyzed Centers for Disease Control (CDC) light trap collections of adult mosquitoes from two collection schemes: one performed as part of a reactive-test-and-treat program and the second performed along a geographical transect. Morphological identification, molecular verification of anopheline species, and blood meal source were determined on individual samples. Data from these collections supported earlier studies demonstrating An. squamosus to be primarily exophagic and zoophilic, allowing them to evade current control measures. The phylogenetic relationships generated from the specimens in this study illustrate the existence of well supported clade structure among An. squamosus specimens, which further emphasizes the importance of molecular identification of vectors. The primarily exophagic behavior of An. squamosus in these collections also highlights that indoor vector control strategies will not be sufficient for elimination of malaria in southern Zambia.

Prevalence of Glucose-6-Phosphate Dehydrogenase Deficiency and Gametocytemia in a Pre-Elimination, Low Malaria Transmission Setting in Southern Zambia

The WHO recommends single low-dose (SLD) primaquine as a gametocytocide to reduce Plasmodium falciparum transmission in areas of low transmission. Despite this recommendation, uptake of SLD primaquine has been low because of concerns of glucose-6-phosphate dehydrogenase (G6PD) deficiency. Individuals with G6PD deficiency can experience hemolysis when exposed to primaquine. In Southern Province, Zambia, malaria transmission has declined significantly over the past decade. Single low-dose primaquine may be an effective tool, but there is limited information on G6PD deficiency. We screened 137 residents in Macha, Southern Province, Zambia, and the prevalence of G6PD (A-) was 15%. We also revisited data collected from 2008 to 2013 in the same area and found the highest gametocyte burden among those aged 5-15 years. The findings from this study suggest that SLD primaquine targeted to school-aged children may be an effective tool to help achieve malaria elimination in southern Zambia.

Sustained Malaria Transmission despite Reactive Screen-and-Treat in a Low-Transmission Area of Southern Zambia

Malaria elimination strategies are designed to more effectively identify and treat infected individuals to interrupt transmission. One strategy, reactive screen-and-treat, starts with passive detection of symptomatic cases at health facilities. Individuals residing within the index case and neighboring households are screened with a malaria rapid diagnostic test (RDT) and treated if positive. However, it is unclear to what extent this strategy is effective in reducing transmission. Reactive screen-and-treat was implemented in Choma district, Southern Province, Zambia, in 2013, in which residents of the index case and neighboring households within 140 m were screened with an RDT. From March 2016 to July 2018, the screening radius was extended to 250-m, and additional follow-up visits at 30 and 90 days were added to evaluate the strategy. Plasmodium falciparum parasite prevalence was measured using an RDT and by quantitative PCR (qPCR). A 24-single nucleotide polymorphism molecular bar-code assay was used to genotype parasites. Eighty-four index case households with 676 residents were enrolled between March 2016 and March 2018. Within each season, parasite prevalence declined significantly in index households at the 30-day visit and remained low at the 90-day visit. However, parasite prevalence was not reduced to zero. Infections identified by qPCR persisted between study visits and were not identified by RDT. Parasites identified within the same household were most genetically related; however, overall parasite relatedness was low and similar across time and space. Thus, despite implementation of a reactive screen-and-treat program, parasitemia was not eliminated, and persisted in targeted households for at least 3 months.

The Typhoid Fever Surveillance in Africa Program: Geospatial Sampling Frames for Household-based Studies: Lessons Learned From a Multicountry Surveillance Network in Senegal, South Africa, and Sudan

Background

Robust household sampling, commonly applied for population-based investigations, requires sampling frames or household lists to minimize selection bias. We have applied Google Earth Pro satellite imagery to constitute structure-based sampling frames at sites in Pikine, Senegal; Pietermaritzburg, South Africa; and Wad-Medani, Sudan. Here we present our experiences in using this approach and findings from assessing its applicability by determining positional accuracy.

Methods

Printouts of satellite imagery combined with Global Positioning System receivers were used to locate and to verify the locations of sample structures (simple random selection; weighted-stratified sampling). Positional accuracy was assessed by study site and administrative subareas by calculating normalized distances (meters) between coordinates taken from the sampling frame and on the ground using receivers. A higher accuracy in conjunction with smaller distances was assumed. Kruskal-Wallis and Dunn multiple pairwise comparisons were performed to evaluate positional accuracy by setting and by individual surveyor in Pietermaritzburg.

Results

The median normalized distances and interquartile ranges were 0.05 and 0.03–0.08 in Pikine, 0.09 and 0.05–0.19 in Pietermaritzburg, and 0.05 and 0.00–0.10 in Wad-Medani, respectively. Root mean square errors were 0.08 in Pikine, 0.42 in Pietermaritzburg, and 0.17 in Wad-Medani. Kruskal-Wallis and Dunn comparisons indicated significant differences by low- and high-density setting and interviewers who performed the presented approach with high accuracy compared to interviewers with poor accuracy.

Conclusions

The geospatial approach presented minimizes systematic errors and increases robustness and representativeness of a sample. However, the findings imply that this approach may not be applicable at all sites and settings; its success also depends on skills of surveyors working with aerial data. Methodological modifications are required, especially for resource-challenged sites that may be affected by constraints in data availability and area size.

Improving the efficiency of reactive case detection for malaria elimination in southern Zambia: a cross-sectional study

Background

Reactive case detection (RCD) seeks to enhance malaria surveillance and control by identifying and treating parasitaemic individuals residing near index cases. In Zambia, this strategy starts with passive detection of symptomatic incident malaria cases at local health facilities or by community health workers, with subsequent home visits to screen-and-treat residents in the index case and neighbouring (secondary) households within a 140-m radius using rapid diagnostic tests (RDTs). However, a small circular radius may not be the most efficient strategy to identify parasitaemic individuals in low-endemic areas with hotspots of malaria transmission. To evaluate if RCD efficiency could be improved by increasing the probability of identifying parasitaemic residents, environmental risk factors and a larger screening radius (250 m) were assessed in a region of low malaria endemicity.

Methods

Between January 12, 2015 and July 26, 2017, 4170 individuals residing in 158 index and 531 secondary households were enrolled and completed a baseline questionnaire in the catchment area of Macha Hospital in Choma District, Southern Province, Zambia. Plasmodium falciparum prevalence was measured using PfHRP2 RDTs and quantitative PCR (qPCR). A Quickbird™ high-resolution satellite image of the catchment area was used to create environmental risk factors in ArcGIS, and generalized estimating equations were used to evaluate associations between risk factors and secondary households with parasitaemic individuals.

Results

The parasite prevalence in secondary (non-index case) households was 0.7% by RDT and 1.8% by qPCR. Overall, 8.5% (n = 45) of secondary households had at least one resident with parasitaemia by qPCR or RDT. The risk of a secondary household having a parasitaemic resident was significantly increased in proximity to higher order streams and marginally with increasing distance from index households. The adjusted OR for proximity to third- and fifth-order streams were 2.97 (95% CI 1.04–8.42) and 2.30 (95% CI 1.04–5.09), respectively, and that for distance to index households for each 50 m was 1.24 (95% CI 0.98–1.58).

Conclusion

Applying proximity to streams as a screening tool, 16% (n = 3) more malaria-positive secondary households were identified compared to using a 140-m circular screening radius. This analysis highlights the potential use of environmental risk factors as a screening strategy to increase RCD efficiency.

Malaria risk assessment and mapping using satellite imagery and boosted regression trees in the Peruvian Amazon

This is the first study to assess the risk of co-endemic Plasmodium vivax and Plasmodium falciparum transmission in the Peruvian Amazon using boosted regression tree (BRT) models based on social and environmental predictors derived from satellite imagery and data. Yearly cross-validated BRT models were created to discriminate high-risk (annual parasite index API > 10 cases/1000 people) and very-high-risk for malaria (API > 50 cases/1000 people) in 2766 georeferenced villages of Loreto department, between 2010-2017 as other parts in the article (graphs, tables, and texts). Predictors were cumulative annual rainfall, forest coverage, annual forest loss, annual mean land surface temperature, normalized difference vegetation index (NDVI), normalized difference water index (NDWI), shortest distance to rivers, time to populated villages, and population density. BRT models built with predictor data of a given year efficiently discriminated the malaria risk for that year in villages (area under the ROC curve (AUC) > 0.80), and most models also effectively predicted malaria risk in the following year. Cumulative rainfall, population density and time to populated villages were consistently the top three predictors for both P. vivax and P. falciparum incidence. Maps created using the BRT models characterize the spatial distribution of the malaria incidence in Loreto and should contribute to malaria-related decision making in the area.

Malaria around large dams in Africa: effect of environmental and transmission endemicity factors

Background

The impact of large dams on malaria has received widespread attention. However, understanding how dam topography and transmission endemicity influence malaria incidences is limited.

Methods

Data from the European Commission’s Joint Research Center and Shuttle Radar Topography Mission were used to determine reservoir perimeters and shoreline slope of African dams. Georeferenced data from the Malaria Atlas Project (MAP) were used to estimate malaria incidence rates in communities near reservoir shorelines. Population data from the WorldPop database were used to estimate the population at risk of malaria around dams in stable and unstable areas.

Results

The data showed that people living near (< 5 km) large dams in sub-Saharan Africa grew from 14.4 million in 2000 to 18.7 million in 2015. Overall, across sub-Saharan Africa between 0.7 and 1.6 million malaria cases per year are attributable to large dams. Whilst annual malaria incidence declined markedly in both stable and unstable areas between 2000 and 2015, the malaria impact of dams appeared to increase in unstable areas, but decreased in stable areas. Shoreline slope was found to be the most important malaria risk factor in dam-affected geographies, explaining 41–82% (P < 0.001) of the variation in malaria incidence around reservoirs.

Conclusion

Gentler, more gradual shoreline slopes were associated with much greater malaria risk. Dam-related environmental variables such as dam topography and shoreline slopes are an important factor that should be considered in efforts to predict and control malaria around dams.

Sampling strategy of an epidemiological survey using a satellite image program

OBJECTIVE

To describe the sampling strategy of an epidemiological survey with the aid of satellite images, including details of the multistage probability sampling process.

METHODS

A probability sample of individuals living in the rural area of Rosário do Sul, state of Rio Grande do Sul, Brazil, aged 15 years old or more, was evaluated. Participants answered questionnaires (medical history, sociodemographic characteristics, habits, alcohol use, quality of life, stress, rumination, and self-perceived periodontal diseases), and were subjected to clinical oral examinations as well as anthropometric measurements (blood pressure, height, weight, abdominal and waist circumferences). Oral evaluation comprehended a complete periodontal exam at six sites per tooth, including the following assessments: furcation involvement; dental abrasion; tooth decay, including the indexing of missing and filled surfaces; O'Brien index; gingival abrasion; oral cavity and lip lesions; complete periapical radiographic exam, and use of prostheses. Besides this oral clinical approach, subgingival plaque, crevicular gingival fluid, saliva, and blood samples were collected. Examiners were trained and calibrated during previous evaluations. A pilot study allowed the logistic of the performed exams to be adjusted as needed.

RESULTS

Among 1,087 eligible individuals, 688 were examined (63.3%). Age, sex, and skin color data were compared to data from the last demographic census (2010) of the Brazilian Institute of Geography and Statistics, which served to validate the sampling strategy.

CONCLUSIONS

The careful methods used in this study, in which satellite images were used in the delimitation of epidemiological areas, ensure the quality of the estimates obtained and allow for these estimates to be used in oral health surveillance and health policies improvements.

Modeling Spatio-temporal Malaria Risk Using Remote Sensing and Environmental Factors

BACKGROUND

Remote sensing have been intensively used across many disciplines, however, such information was limited in spatial epidemiology.

METHODS

Two years (2009 & 2010) Landsat TM satellite data was used to develop vegetation, water bodies, air temperature and humidity criterion maps to model malaria risk and its spatiotemporal seasonal variation. The criterion maps were used in weighted overlay analysis to generate final categorized malaria risk map.

RESULTS

Overall, 25%, 68%, 18% and 16% of the total area of Rawalpindi region was categorized as danger zone for Jun 2009, Oct 2009, Jan 2010 and Jun 2010, respectively. The malaria risk reached at its peak during the monsoon season whereas air temperature and relative humidity were the main contributing factors in seasonal variation.

CONCLUSION

Malaria risk maps could be used for prioritizing areas for malaria control measures.

Applications of Space Technologies to Global Health: Scoping Review

Background

Space technology has an impact on many domains of activity on earth, including in the field of global health. With the recent adoption of the United Nations’ Sustainable Development Goals that highlight the need for strengthening partnerships in different domains, it is useful to better characterize the relationship between space technology and global health.

Objective

The aim of this study was to identify the applications of space technologies to global health, the key stakeholders in the field, as well as gaps and challenges.

Methods

We used a scoping review methodology, including a literature review and the involvement of stakeholders, via a brief self-administered, open-response questionnaire. A distinct search on several search engines was conducted for each of the four key technological domains that were previously identified by the UN Office for Outer Space Affairs’ Expert Group on Space and Global Health (Domain A: remote sensing; Domain B: global navigation satellite systems; Domain C: satellite communication; and Domain D: human space flight). Themes in which space technologies are of benefit to global health were extracted. Key stakeholders, as well as gaps, challenges, and perspectives were identified.

Results

A total of 222 sources were included for Domain A, 82 sources for Domain B, 144 sources for Domain C, and 31 sources for Domain D. A total of 3 questionnaires out of 16 sent were answered. Global navigation satellite systems and geographic information systems are used for the study and forecasting of communicable and noncommunicable diseases; satellite communication and global navigation satellite systems for disaster response; satellite communication for telemedicine and tele-education; and global navigation satellite systems for autonomy improvement, access to health care, as well as for safe and efficient transportation. Various health research and technologies developed for inhabited space flights have been adapted for terrestrial use.

Conclusions

Although numerous examples of space technology applications to global health exist, improved awareness, training, and collaboration of the research community is needed.

Efficiency of a Malaria Reactive Test-and-Treat Program in Southern Zambia: A Prospective, Observational Study

To improve malaria surveillance and achieve elimination, the Zambian National Malaria Elimination Program implemented a reactive test-and-treat program in Southern Province in 2013 in which individuals with rapid diagnostic test (RDT)-confirmed malaria are followed-up at their home within 1 week of diagnosis. Individuals present at the index case household and those residing within 140 m of the index case are tested with an RDT and treated with artemether-lumefantrine if positive. This study evaluated the efficiency of this reactive test-and-treat strategy by characterizing infected individuals missed by the RDT and the current screening radius. The radius was expanded to 250 m, and a quantitative polymerase chain reaction (qPCR) test was performed on dried blood spot specimens. From January 2015 through March 2016, 145 index cases were identified at health centers and health posts. A total of 3,333 individuals residing in 525 households were screened. Excluding index cases, the parasite prevalence was 1.1% by RDT (33 positives of 3,016 participants) and 2.4% by qPCR (73 positives of 3,016 participants). Of the qPCR-positive cases, 62% of 73 individuals tested negative by RDT. Approximately half of the infected individuals resided within the index case household (58% of RDT-positive individuals and 48% of qPCR-positive individuals). The low sensitivity of the RDT and the high proportion of secondary cases within the index case household decreased the efficiency of this reactive test-and-treat strategy. Reactive focal drug administration in index case households would be a more efficient approach to treating infected individuals associated with a symptomatic case.

House Structure Is Associated with Plasmodium falciparum Infection in a Low-Transmission Setting in Southern Zambia

House structure may influence the risk of malaria by affecting mosquito entry and indoor resting. Identification of construction features associated with protective benefits could inform vector control approaches, even in low-transmission settings. We examined the association between house structure and malaria prevalence in a cross-sectional analysis of 2,788 children and adults residing in 866 houses in a low-transmission area of Southern Province, Zambia, over the period 2008-2012. Houses were categorized according to wall (brick/cement block or mud/grass) and roof (metal or grass) material. Malaria was assessed by point-of-care rapid diagnostic test (RDT) for Plasmodium falciparum. We identified 52 RDT-positive individuals residing in 41 houses, indicating an overall prevalence in the sample of 1.9%, ranging from 1.4% to 8.8% among the different house types. Occupants of higher quality houses had reduced odds of P. falciparum malaria compared with those in the lowest quality houses after controlling for bed net use, indoor insecticide spraying, clustering by house, cohabitation with another RDT-positive individual, transmission season, ecologic risk defined as nearest distance to a Strahler-classified third-order stream, education, age, and gender (adjusted odds ratio [OR]: 0.26, 95% confidence interval [CI]: 0.09-0.73, P = 0.01 for houses with brick/cement block walls and metal roof; OR: 0.22, 95% CI: 0.09-0.52, P < 0.01 for houses with brick/cement block walls and grass roof). Housing improvements offer a promising approach to vector control in low-transmission settings that circumvents the threat posed by insecticide resistance, and may confer a protective benefit of similar magnitude to current vector control strategies.

Characterizing and quantifying human movement patterns using GPS data loggers in an area approaching malaria elimination in rural southern Zambia

In areas approaching malaria elimination, human mobility patterns are important in determining the proportion of malaria cases that are imported or the result of low-level, endemic transmission. A convenience sample of participants enrolled in a longitudinal cohort study in the catchment area of Macha Hospital in Choma District, Southern Province, Zambia, was selected to carry a GPS data logger for one month from October 2013 to August 2014. Density maps and activity space plots were created to evaluate seasonal movement patterns. Time spent outside the household compound during anopheline biting times, and time spent in malaria high- and low-risk areas, were calculated. There was evidence of seasonal movement patterns, with increased long-distance movement during the dry season. A median of 10.6% (interquartile range (IQR): 5.8-23.8) of time was spent away from the household, which decreased during anopheline biting times to 5.6% (IQR: 1.7-14.9). The per cent of time spent in malaria high-risk areas for participants residing in high-risk areas ranged from 83.2% to 100%, but ranged from only 0.0% to 36.7% for participants residing in low-risk areas. Interventions targeted at the household may be more effective because of restricted movement during the rainy season, with limited movement between high- and low-risk areas.

Distinct parasite populations infect individuals identified through passive and active case detection in a region of declining malaria transmission in southern Zambia

BACKGROUND

Substantial reductions in the burden of malaria have been documented in parts of sub-Saharan Africa, with elimination strategies and goals being formulated in some regions. Within this context, understanding the epidemiology of low-level malaria transmission is crucial to achieving and sustaining elimination. A 24 single-nucleotide-polymorphism Plasmodium falciparum molecular barcode was used to characterize parasite populations from infected individuals identified through passive and active case detection in an area approaching malaria elimination in southern Zambia.

METHODS

The study was conducted in the catchment area of Macha Hospital in Choma District, Southern Province, Zambia, where the parasite prevalence declined over the past decade, from 9.2% in 2008 to less than 1% in 2013. Parasite haplotypes from actively detected, P. falciparum-infected participants enrolled in a serial cross-sectional, community-based cohort study from 2008 to 2013 and from passively detected, P. falciparum-infected individuals enrolled at five rural health centres from 2012 to 2015 were compared. Changes in P. falciparum genetic relatedness, diversity and complexity were analysed as malaria transmission declined.

RESULTS

Actively detected cases identified in the community were most commonly rapid diagnostic test negative, asymptomatic and had submicroscopic parasitaemia. Phylogenetic reconstruction using concatenated 24 SNP barcode revealed a separation of parasite haplotypes from passively and actively detected infections, consistent with two genetically distinct parasite populations. For passively detected infections identified at health centres, the proportion of detectable polyclonal infections was consistently low in all seasons, in contrast with actively detected infections in which the proportion of polyclonal infections was high. The mean genetic divergence for passively detected infections was 34.5% for the 2012-2013 transmission season, 37.8% for the 2013-2014 season, and 30.8% for the 2014-2015 season. The mean genetic divergence for actively detected infections was 22.3% in the 2008 season and 29.0% in the 2008-2009 season and 9.9% across the 2012-2014 seasons.

CONCLUSIONS

Distinct parasite populations were identified among infected individuals identified through active and passive surveillance, suggesting that infected individuals detected through active surveillance may not have contributed substantially to ongoing transmission. As parasite prevalence and diversity within these individuals declined, resource-intensive efforts to identify the chronically infected reservoir may not be necessary to eliminate malaria in this setting.

Spatial clustering and risk factors of malaria infections in Bata district, Equatorial Guinea

Background

The transmission of malaria is intense in the majority of the countries of sub-Saharan Africa, particularly in those that are located along the Equatorial strip. The present study aimed to describe the current distribution of malaria prevalence among children and its environment-related factors as well as to detect malaria spatial clusters in the district of Bata, in Equatorial Guinea.

Methods

From June to August 2013 a representative cross-sectional survey using a multistage, stratified, cluster-selected sample was carried out of children in urban and rural areas of Bata District. All children were tested for malaria using rapid diagnostic tests (RDTs). Results were linked to each household by global position system data. Two cluster analysis methods were used: hot spot analysis using the Getis-Ord Gi statistic, and the SaTScan™ spatial statistic estimates, based on the assumption of a Poisson distribution to detect spatial clusters. In addition, univariate associations and Poisson regression model were used to explore the association between malaria prevalence at household level with different environmental factors.

Results

A total of 1416 children aged 2 months to 15 years living in 417 households were included in this study. Malaria prevalence by RDTs was 47.53%, being highest in the age group 6–15 years (63.24%, p < 0.001). Those children living in rural areas were there malaria risk is greater (65.81%) (p < 0.001). Malaria prevalence was higher in those houses located <1 km from a river and <3 km to a forest (IRR: 1.31; 95% CI 1.13–1.51 and IRR: 1.44; 95% CI 1.25–1.66, respectively). Poisson regression analysis also showed a decrease in malaria prevalence with altitude (IRR: 0.73; 95% CI 0.62–0.86). A significant cluster inland of the district, in rural areas has been found.

Conclusions

This study reveals a high prevalence of RDT-based malaria among children in Bata district. Those households situated in inland rural areas, near to a river, a green area and/or at low altitude were a risk factor for malaria. Spatial tools can help policy makers to promote new recommendations for malaria control.

Measles and Rubella Seroprevalence Among HIV-infected and Uninfected Zambian Youth

BACKGROUND

Measles and congenital rubella syndrome remain significant causes of morbidity and mortality despite available vaccines. HIV-infected youth may be at increased risk of measles because of greater waning immunity after vaccination. At a population level, they constitute a potentially large pool of susceptibles to measles and rubella. More data among HIV-infected youth in sub-Saharan Africa are needed to guide vaccination policy and control strategies.

METHODS

This cross-sectional study was nested within 2 ongoing studies of malaria and HIV in Zambia. Dried blood spot cards from youth (5-15 years) in these studies from 2009 to 2013 were tested for IgG antibodies to measles and rubella viruses. HIV-uninfected youth, HIV-infected treatment-naive youth and HIV-infected youth receiving antiretroviral therapy (ART) were compared.

RESULTS

A total of 617 HIV-uninfected, 144 HIV-infected treatment-naive and 128 HIV-infected youth receiving ART were included in this study. The proportion seropositive for measles virus was significantly higher among HIV-uninfected youth (92.5%) compared with HIV-infected treatment-naive youth (74.1%) and HIV-infected youth receiving ART (71.9%). No differences by age were observed. The proportion seropositive for rubella virus was significantly higher among HIV-uninfected youth (54.7%) compared with HIV-infected treatment-naive youth (41.7%) and HIV-infected youth receiving ART (49.6%), with increases observed by age for all groups.

CONCLUSIONS

Measles seroprevalence was lower among HIV-infected than uninfected youth, consistent with waning immunity after measles vaccination. HIV-infected youth would benefit from revaccination. Half of all youth in rural Zambia were susceptible to rubella and may need targeting for catch-up rubella campaigns when measles-rubella vaccine is introduced.

Detection of Plasmodium falciparum Infection in Anopheles squamosus (Diptera: Culicidae) in an Area Targeted for Malaria Elimination, Southern Zambia

Southern Zambia is the focus of strategies to create malaria-free zones. Interventions being rolled out include test and treat strategies and distribution of insecticide-treated bed nets that target vectors that host-seek indoors and late at night. In Macha, Choma District, collections of mosquitoes were made outdoors using barrier screens within homesteads or UV bulb light traps set next to goats, cattle, or chickens during the rainy season of 2015. Anopheline mosquitoes were identified to species using molecular methods and Plasmodium falciparum infectivity was determined by ELISA and real-time qPCR methods. More than 40% of specimens caught were identified as Anopheles squamosus Theobald, 1901 of which six were found harboring malaria parasites. A single sample, morphologically identified as Anopheles coustani Laveran, 1900, was also found to be infectious. All seven specimens were caught outdoors next to goat pens. Parasite-positive specimens as well as a subset of An. squamosus specimens from either the same study or archive collections from the same area underwent sequencing of the mitochondrial cytochrome oxidase subunit I gene. Maximum parsimony trees constructed from the aligned sequences indicated presence of at least two clades of An. squamosus with infectious specimens falling in each clade. The single infectious specimen identified morphologically as An. coustani could not be matched to reference sequences. This is the first report from Zambia of infections in An. squamosus, a species which is described in literature to display exophagic traits. The bionomic characteristics of this species needs to be studied further to fully evaluate the implications for indoor-targeted vector control.

Evaluation of the operational challenges in implementing reactive screen-and-treat and implications of reactive case detection strategies for malaria elimination in a region of low transmission in southern Zambia

Background

As malaria transmission declines in many regions of sub-Saharan Africa, interventions to identify the asymptomatic reservoir are being deployed with the goals of improving surveillance and interrupting transmission. Reactive case detection strategies, in which individuals with clinical malaria are followed up at their home and household residents and neighbours are screened and treated for malaria, are increasingly used as part of malaria elimination programmes.

Methods

A reactive screen-and-treat programme was implemented by the National Malaria Control Centre in Southern Province, Zambia, in which individuals residing within 140 m of an index case were screened with a malaria rapid diagnostic test (RDT) and treated if positive. The operational challenges during the early stages of implementing this reactive screen-and-treat programme in the catchment area of Macha Hospital in Southern Province, Zambia were assessed using rural health centre records, ground truth evaluation of community health worker performance, and data from serial cross-sectional surveys. The proportion of individuals infected with Plasmodium falciparum who were identified and treated was estimated by simulating reactive screen-and-treat and focal drug administration cascades.

Results

Within the 1st year of implementation, community health workers followed up 32 % of eligible index cases. When index cases were followed up, 66 % of residents were at home in the index households and 58 % in neighbouring households. Forty-one neighbouring households of 26 index households were screened, but only 13 (32 %) were within the 140-m screening radius. The parasite prevalence by RDT was 22 % in index households and 5 % in neighbouring households. In a simulation model with complete follow-up, 22 % of the total infected population would be detected with reactive screen-and-treat but 57 % with reactive focal drug administration.

Conclusions

With limited resources, coverage and diagnostic tools, reactive screen-and-treat will likely not be sufficient to achieve malaria elimination in this setting. However, high coverage with reactive focal drug administration could be efficient at decreasing the reservoir of infection and should be considered as an alternative strategy.

Electronic supplementary material

The online version of this article (doi:10.1186/s12936-016-1460-x) contains supplementary material, which is available to authorized users.

Spatial and temporal changes in household structure locations using high-resolution satellite imagery for population assessment: an analysis in southern Zambia, 2006-2011

Satellite imagery is increasingly available at high spatial resolution and can be used for various purposes in public health research and programme implementation. Comparing a census generated from two satellite images of the same region in rural southern Zambia obtained four and a half years apart identified patterns of household locations and change over time. The length of time that a satellite image-based census is accurate determines its utility. Households were enumerated manually from satellite images obtained in 2006 and 2011 of the same area. Spatial statistics were used to describe clustering, cluster detection, and spatial variation in the location of households. A total of 3821 household locations were enumerated in 2006 and 4256 in 2011, a net change of 435 houses (11.4% increase). Comparison of the images indicated that 971 (25.4%) structures were added and 536 (14.0%) removed. Further analysis suggested similar household clustering in the two images and no substantial difference in concentration of households across the study area. Cluster detection analysis identified a small area where significantly more household structures were removed than expected; however, the amount of change was of limited practical significance. These findings suggest that random sampling of households for study participation would not induce geographic bias if based on a 4.5-year-old image in this region. Application of spatial statistical methods provides insights into the population distribution changes between two time periods and can be helpful in assessing the accuracy of satellite imagery.

Individual- and Household-Level Risk Factors Associated with Malaria in Mutasa District, Zimbabwe: A Serial Cross-Sectional Study

Malaria constitutes a major public health problem in Zimbabwe, particularly in the north and east bordering Zambia and Mozambique. In Manicaland Province in eastern Zimbabwe, malaria transmission is seasonal and unstable. Over the past decade, Manicaland Province has reported increased malaria transmission due to limited funding, drug resistance and insecticide resistance. The aim of this study was to identify risk factors at the individual and household levels to better understand the epidemiology of malaria and guide malaria control strategies in eastern Zimbabwe. Between October 2012 and September 2014, individual demographic data and household characteristics were collected from cross-sectional surveys of 1,116 individuals residing in 316 households in Mutasa District, one of the worst affected districts. Factors associated with malaria, measured by rapid diagnostic test (RDT), were identified through multilevel logistic regression models. A total of 74 participants were RDT positive. Sleeping under a bed net had a protective effect against malaria despite pyrethroid resistance in the mosquito vector. Multivariate analysis showed that malaria risk was higher among individuals younger than 25 years, residing in households located at a lower household density and in closer proximity to the Mozambique border. The risk factors identified need to be considered in targeting malaria control interventions to reduce host-vector interactions.

High-Resolution Plasmodium falciparum Malaria Risk Mapping in Mutasa District, Zimbabwe: Implications for Regaining Control

In Zimbabwe, more than half of malaria cases are concentrated in Manicaland Province, where seasonal malaria epidemics occur despite intensified control strategies. The objectives of this study were to develop a prediction model based on environmental risk factors and obtain seasonal malaria risk maps for Mutasa District, one of the worst affected districts in Manicaland Province. From October 2012 to September 2015, 483 households were surveyed, and 104 individuals residing within 69 households had positive rapid diagnostic test results. Logistic regression was used to model the probability of household positivity as a function of the environmental covariates extracted from high-resolution remote sensing data sources. Model predictions and prediction standard errors were generated for the rainy and dry seasons. The resulting maps predicted elevated risk during the rainy season, particularly in low-lying areas bordering Mozambique. In contrast, the risk of malaria was low across the study area during the dry season with foci of malaria risk scattered along the northern and western peripheries of the study area. These findings underscore the need for strong cross-border malaria control initiatives to complement country-specific interventions.

Reduction in Malaria Incidence following Indoor Residual Spraying with Actellic 300 CS in a Setting with Pyrethroid Resistance: Mutasa District, Zimbabwe

Background

More than half of malaria cases in Zimbabwe are concentrated in Manicaland Province, where seasonal malaria epidemics occur despite intensified control strategies. Recently, high levels of pyrethroid and carbamate resistance were detected in Anopheles funestus, the major malaria vector in eastern Zimbabwe. In response, a single round of indoor residual spraying (IRS) using pirimiphos-methyl (an organophosphate) was implemented in four high burden districts of Manicaland Province from November 1, 2014 to December 19, 2014. The objective of this study was to evaluate the effect of this programmatic switch in insecticides on malaria morbidity reported from health care facilities in Mutasa District, one of the worst affected districts in Manicaland Province.

Methods

The number of weekly malaria cases for each health facility 24 months prior to the 2014 IRS campaign and in the subsequent high transmission season were obtained from passive case surveillance. Environmental variables were extracted from remote-sensing data sources and linked to each health care facility. Negative binomial regression was used to model the weekly number of malaria cases, adjusted for seasonality and environmental variables.

Results

From December 2012 to May 2015, 124,206 malaria cases were reported from 42 health care facilities in Mutasa District. Based on a higher burden of malaria, 20 out of 31 municipal wards were sprayed in the district. Overall, 87.3% of target structures were sprayed and 92.1% of the target population protected. During the 6 months after the 2014 IRS campaign, a period when transmission would have otherwise peaked, the incidence of malaria was 38% lower than the preceding 24 months at health facilities in the sprayed wards.

Conclusions

Pirimiphos-methyl had a measurable impact on malaria incidence and is an effective insecticide for the control of An. funestus in eastern Zimbabwe.

Utilization of Healthcare in the Typhoid Fever Surveillance in Africa Program

BACKGROUND

Assessing healthcare utilization is important to identify weaknesses of healthcare systems, to outline action points for preventive measures and interventions, and to more accurately estimate the disease burden in a population.

METHODS

A healthcare utilization survey was developed for the Typhoid Fever Surveillance in Africa Program (TSAP) to adjust incidences of salmonellosis determined through passive, healthcare facility-based surveillance. This cross-sectional survey was conducted at 11 sites in 9 sub-Saharan African countries. Demographic data and healthcare-seeking behavior were assessed at selected households. Overall and age-stratified percentages of each study population that sought healthcare at a TSAP healthcare facility and elsewhere were determined.

RESULTS

Overall, 88% (1007/1145) and 81% (1811/2238) of the population in Polesgo and Nioko 2, Burkina Faso, respectively, and 63% (1636/2590) in Butajira, Ethiopia, sought healthcare for fever at any TSAP healthcare facility. A far smaller proportion-namely, 20%-45% of the population in Bissau, Guinea-Bissau (1743/3885), Pikine, Senegal (1473/4659), Wad-Medani, Sudan (861/3169), and Pietermaritzburg, South Africa (667/2819); 18% (483/2622) and 9% (197/2293) in Imerintsiatosika and Isotry, Madagascar, respectively; and 4% (127/3089) in Moshi, Tanzania-sought healthcare at a TSAP healthcare facility. Patients with fever preferred to visit pharmacies in Imerintsiatosika and Isotry, and favored self-management of fever in Moshi. Age-dependent differences in healthcare utilization were also observed within and across sites.

CONCLUSIONS

Healthcare utilization for fever varied greatly across sites, and revealed that not all studied populations were under optimal surveillance. This demonstrates the importance of assessing healthcare utilization. Survey data were pivotal for the adjustment of the program's estimates of salmonellosis and other conditions associated with fever.

Reactive case-detection of malaria in Pailin Province, Western Cambodia: lessons from a year-long evaluation in a pre-elimination setting

Background

As momentum towards malaria elimination grows, strategies are being developed for scale-up in elimination settings. One prominent strategy, reactive case detection (RACD), involves screening and treating individuals living in close proximity to passively detected, or “index” cases. This study aims to use RACD to quantify Plasmodium parasitaemia in households of index cases, and identify risk factors for infection; these data could inform reactive screening approaches and identify target risk groups.

Methods

This study was conducted in the Western Cambodian province of Pailin between May 2013 and March 2014 among 440 households. Index participants/index cases (n = 270) and surrounding households (n = 110) were screened for Plasmodium infection with rapid diagnostic tests (RDT), microscopy and real-time polymerase chain reaction (PCR). Participants were interviewed to identify risk factors. A comparison group of 60 randomly-selected households was also screened, to compare infection levels of RACD and non-RACD households. In order to identify potential risk factors that would inform screening approaches and identify risk groups, multivariate logistic regression models were applied.

Results

Nine infections were identified in households of index cases (RACD approach) through RDT screening of 1898 individuals (seven Plasmodium vivax, two Plasmodium falciparum); seven were afebrile. Seventeen infections were identified through PCR screening of 1596 individuals (15 P. vivax, and 22 % P. falciparum/P. vivax mixed infections). In the control group, 25 P. falciparum infections were identified through PCR screening of 237 individuals, and no P. vivax was found. Plasmodium falciparum infection was associated with fever (p = 0.013), being a member of a control household (p ≤ 0.001), having a history of malaria infection (p = 0.041), and sleeping without a mosquito net (p = 0.011). Significant predictors of P. vivax infection, as diagnosed by PCR, were fever (p = 0.058, borderline significant) and history of malaria infection (p ≤ 0.001).

Conclusion

This study found that RACD identified very few secondary infections when targeting index and neighbouring households for screening. The results suggest RACD is not appropriate, where exposure to malaria occurs away from the community, and there is a high level of treatment-seeking from the private sector. Piloting RACD in a range of transmission settings would help to identify the ideal environment for feasible and effective reactive screening methods.

Predictive Malaria Risk and Uncertainty Mapping in Nchelenge District, Zambia: Evidence of Widespread, Persistent Risk and Implications for Targeted Interventions

Malaria risk maps may be used to guide policy decisions on whether vector control interventions should be targeted and, if so, where. Active surveillance for malaria was conducted through household surveys in Nchelenge District, Zambia from April 2012 through December 2014. Households were enumerated based on satellite imagery and randomly selected for study enrollment. At each visit, participants were administered a questionnaire and a malaria rapid diagnostic test (RDT). Logistic regression models were used to construct spatial prediction risk maps and maps of risk uncertainty. A total of 461 households were visited, comprising 1,725 participants, of whom 48% were RDT positive. Several environmental features were associated with increased household malaria risk in a multivariable logistic regression model adjusting for seasonal variation. The model was validated using both internal and external evaluation measures to generate and assess root mean square error, as well as sensitivity and specificity for predicted risk. The final, validated model was used to predict and map malaria risk including a measure of risk uncertainty. Malaria risk in a high, perennial transmission setting is widespread but heterogeneous at a local scale, with seasonal variation. Targeting malaria control interventions may not be appropriate in this epidemiological setting.

Factors Associated with Sustained Use of Long-Lasting Insecticide-Treated Nets Following a Reduction in Malaria Transmission in Southern Zambia

Understanding factors influencing sustained use of long-lasting insecticide-treated nets (LLIN) in areas of declining malaria transmission is critical to sustaining control and may facilitate elimination. From 2008 to 2013, 655 households in Choma District, Zambia, were randomly selected and residents were administered a questionnaire and malaria rapid diagnostic test. Mosquitoes were collected concurrently by light trap. In a multilevel model, children and adolescents of 5-17 years of age were 55% less likely to sleep under LLIN than adults (odds ratio [OR] = 0.45; 95% confidence interval [CI] = 0.35, 0.58). LLIN use was 80% higher during the rainy season (OR = 1.8; CI = 1.5, 2.2) and residents of households with three or more nets were over twice as likely to use a LLIN (OR = 2.1; CI = 1.4, 3.1). For every increase in 0.5 km from the nearest health center, the odds of LLIN use decreased 9% (OR = 0.9; CI = 0.88, 0.98). In a second multilevel model, the odds of LLIN use were more than twice high if more than five mosquitoes (anopheline and culicine) were captured in the house compared with households with no mosquitoes captured (OR = 2.1; CI = 1.1, 3.9). LLIN use can be sustained in low-transmission settings with continued education and distributions, and may be partially driven by the presence of nuisance mosquitoes.

Joint spatial Bayesian modeling for studies combining longitudinal and cross-sectional data

Design for intervention studies may combine longitudinal data collected from sampled locations over several survey rounds and cross-sectional data from other locations in the study area. In this case, modeling the impact of the intervention requires an approach that can accommodate both types of data, accounting for the dependence between individuals followed up over time. Inadequate modeling can mask intervention effects, with serious implications for policy making. In this paper we use data from a large-scale larviciding intervention for malaria control implemented in Dar es Salaam, United Republic of Tanzania, collected over a period of almost 5 years. We apply a longitudinal Bayesian spatial model to the Dar es Salaam data, combining follow-up and cross-sectional data, treating the correlation in longitudinal observations separately, and controlling for potential confounders. An innovative feature of this modeling is the use of Ornstein-Uhlenbeck process to model random time effects. We contrast the results with other Bayesian modeling formulations, including cross-sectional approaches that consider individual-level random effects to account for subjects followed up in two or more surveys. The longitudinal modeling approach indicates that the intervention significantly reduced the prevalence of malaria infection in Dar es Salaam by 20% whereas the joint model did not suggest significance within the results. Our results suggest that the longitudinal model is to be preferred when longitudinal information is available at the individual level.

Modeling the distribution of the West Nile and Rift Valley Fever vector Culex pipiens in arid and semi-arid regions of the Middle East and North Africa

BACKGROUND

The Middle East North Africa (MENA) region is under continuous threat of the re-emergence of West Nile virus (WNV) and Rift Valley Fever virus (RVF), two pathogens transmitted by the vector species Culex pipiens. Predicting areas at high risk for disease transmission requires an accurate model of vector distribution, however, most Cx. pipiens distribution modeling has been confined to temperate, forested habitats. Modeling species distributions across a heterogeneous landscape structure requires a flexible modeling method to capture variation in mosquito response to predictors as well as occurrence data points taken from a sufficient range of habitat types.

METHODS

We used presence-only data from Egypt and Lebanon to model the population distribution of Cx. pipiens across a portion of the MENA that also encompasses Jordan, Syria, and Israel. Models were created with a set of environmental predictors including bioclimatic data, human population density, hydrological data, and vegetation indices, and built using maximum entropy (Maxent) and boosted regression tree (BRT) methods. Models were created with and without the inclusion of human population density.

RESULTS

Predictions of Maxent and BRT models were strongly correlated in habitats with high probability of occurrence (Pearson's r=0.774, r=0.734), and more moderately correlated when predicting into regions that exceeded the range of the training data (r=0.666,r=0.558). All models agreed in predicting high probability of occupancy around major urban areas, along the banks of the Nile, the valleys of Israel, Lebanon, and Jordan, and southwestern Saudi Arabia. The most powerful predictors of Cx. pipiens habitat were human population density (60.6% Maxent models, 34.9% BRT models) and the seasonality of the enhanced vegetation index (EVI) (44.7% Maxent, 16.3% BRT). Maxent models tended to be dominated by a single predictor. Areas of high probability corresponded with sites of independent surveys or previous disease outbreaks.

CONCLUSIONS

Cx. pipiens occurrence was positively associated with areas of high human population density and consistent vegetation cover, but was not significantly driven by temperature and rainfall, suggesting human-induced habitat change such as irrigation and urban infrastructure has a greater influence on vector distribution in this region than in temperate zones.

Remotely-sensed, nocturnal, dew point correlates with malaria transmission in Southern Province, Zambia: a time-series study

BACKGROUND

Plasmodium falciparum transmission has decreased significantly in Zambia in the last decade. The malaria transmission is influenced by environmental variables. Incorporation of environmental variables in models of malaria transmission likely improves model fit and predicts probable trends in malaria disease. This work is based on the hypothesis that remotely-sensed environmental factors, including nocturnal dew point, are associated with malaria transmission and sustain foci of transmission during the low transmission season in the Southern Province of Zambia.

METHODS

Thirty-eight rural health centres in Southern Province, Zambia were divided into three zones based on transmission patterns. Correlations between weekly malaria cases and remotely-sensed nocturnal dew point, nocturnal land surface temperature as well as vegetation indices and rainfall were evaluated in time-series analyses from 2012 week 19 to 2013 week 36. Zonal as well as clinic-based, multivariate, autoregressive, integrated, moving average (ARIMAX) models implementing environmental variables were developed to model transmission in 2011 week 19 to 2012 week 18 and forecast transmission in 2013 week 37 to week 41.

RESULTS

During the dry, low transmission season significantly higher vegetation indices, nocturnal land surface temperature and nocturnal dew point were associated with the areas of higher transmission. Environmental variables improved ARIMAX models. Dew point and normalized differentiated vegetation index were significant predictors and improved all zonal transmission models. In the high-transmission zone, this was also seen for land surface temperature. Clinic models were improved by adding dew point and land surface temperature as well as normalized differentiated vegetation index. The mean average error of prediction for ARIMAX models ranged from 0.7 to 33.5%. Forecasts of malaria incidence were valid for three out of five rural health centres; however, with poor results at the zonal level.

CONCLUSIONS

In this study, the fit of ARIMAX models improves when environmental variables are included. There is a significant association of remotely-sensed nocturnal dew point with malaria transmission. Interestingly, dew point might be one of the factors sustaining malaria transmission in areas of general aridity during the dry season.

Validation of three geolocation strategies for health-facility attendees for research and public health surveillance in a rural setting in western Kenya

Understanding the spatial distribution of disease is critical for effective disease control. Where formal address networks do not exist, tracking spatial patterns of clinical disease is difficult. Geolocation strategies were tested at rural health facilities in western Kenya. Methods included geocoding residence by head of compound, participatory mapping and recording the self-reported nearest landmark. Geocoding was able to locate 72·9% [95% confidence interval (CI) 67·7–77·6] of individuals to within 250 m of the true compound location. The participatory mapping exercise was able to correctly locate 82·0% of compounds (95% CI 78·9–84·8) to a 2 × 2·5 km area with a 500 m buffer. The self-reported nearest landmark was able to locate 78·1% (95% CI 73·8–82·1) of compounds to the correct catchment area. These strategies tested provide options for quickly obtaining spatial information on individuals presenting at health facilities.

High burden of malaria following scale-up of control interventions in Nchelenge District, Luapula Province, Zambia

BACKGROUND

Malaria control interventions have been scaled-up in Zambia in conjunction with a malaria surveillance system. Although substantial progress has been achieved in reducing morbidity and mortality, national and local information demonstrated marked heterogeneity in the impact of malaria control across the country. This study reports the high burden of malaria in Nchelenge District, Luapula Province, Zambia from 2006 to 2012 after seven years of control measures.

METHODS

Yearly aggregated information on cases of malaria, malaria deaths, use of malaria diagnostics, and malaria control interventions from 2006 to 2012 were obtained from the Nchelenge District Health Office. Trends in the number of malaria cases, methods of diagnosis, malaria positivity rate among pregnant women, and intervention coverage were analysed using descriptive statistics.

RESULTS

Malaria prevalence remained high, increasing from 38% in 2006 to 53% in 2012. Increasing numbers of cases of severe malaria were reported until 2010. Intense seasonal malaria transmission was observed with seasonal declines in the number of cases between April and August, although malaria transmission continued throughout the year. Clinical diagnosis without accompanying confirmation declined from 95% in 2006 to 35% in 2012. Intervention coverage with long-lasting insecticide-treated nets and indoor residual spraying increased from 2006 to 2012.

CONCLUSIONS

Despite high coverage with vector control interventions, the burden of malaria in Nchelenge District, Zambia remained high. The high parasite prevalence could accurately reflect the true burden, perhaps in part as a consequence of population movement, or improved access to care and case reporting. Quality information at fine spatial scales will be critical for targeting effective interventions and measurement of progress.

Battling Malaria in Rural Zambia with Modern Technology: A Qualitative Study on the Value of Cell Phones, Geographical Information Systems, Asymptomatic Carriers and Rapid Diagnostic Tests to Identify, Treat and Control Malaria

During the last decade much progress has been made in reducing malaria transmission in Macha, Southern Province, Zambia. Introduction of artemisinin combination therapies as well as mass screenings of asymptomatic carriers is believed to have contributed the most. When an endemic malaria situation is moving towards a non-endemic situation the resident population loses acquired immunity and therefore active case detection and efficient surveillance is crucial to prevent epidemic outbreaks. Our purpose was to evaluate the impact of cell phone surveillance and geographical information systems on malaria control in Macha. Furthermore, it evaluates what screening and treatment of asymptomatic carriers and implementation of rapid diagnostic tests in rural health care has led to. Ten in-depth semi-structured interviews, field observations and data collection were performed at the Macha Research Trust and at surrounding rural health centers. This qualitative method was inspired by rapid assessment procedure. The cell phone surveillance has been easily integrated in health care, and its integration with Geographical Information Systems has provided the ability to follow malaria transmission on a weekly basis. In addition, active case detection of asymptomatic carriers has been fruitful, which is reflected in it soon being applied nationwide. Furthermore, rapid diagnostic tests have provided rural health centers with reliable malaria diagnostics, thereby decreasing excessive malaria treatments and selection for drug resistance. This report reflects the importance of asymptomatic carriers in targeting malaria elimination, as well as development of effective surveillance systems when transmission decreases. Such an approach would be cost-efficient in the long run through positive effects in reduced child mortality and relief in health care.

Geographic information systems and logistic regression for high-resolution malaria risk mapping in a rural settlement of the southern Brazilian Amazon

BACKGROUND

In Brazil, 99% of the cases of malaria are concentrated in the Amazon region, with high level of transmission. The objectives of the study were to use geographic information systems (GIS) analysis and logistic regression as a tool to identify and analyse the relative likelihood and its socio-environmental determinants of malaria infection in the Vale do Amanhecer rural settlement, Brazil.

METHODS

A GIS database of georeferenced malaria cases, recorded in 2005, and multiple explanatory data layers was built, based on a multispectral Landsat 5 TM image, digital map of the settlement blocks and a SRTM digital elevation model. Satellite imagery was used to map the spatial patterns of land use and cover (LUC) and to derive spectral indices of vegetation density (NDVI) and soil/vegetation humidity (VSHI). An Euclidian distance operator was applied to measure proximity of domiciles to potential mosquito breeding habitats and gold mining areas. The malaria risk model was generated by multiple logistic regression, in which environmental factors were considered as independent variables and the number of cases, binarized by a threshold value was the dependent variable.

RESULTS

Out of a total of 336 cases of malaria, 133 positive slides were from inhabitants at Road 08, which corresponds to 37.60% of the notifications. The southern region of the settlement presented 276 cases and a greater number of domiciles in which more than ten cases/home were notified. From these, 102 (30.36%) cases were caused by Plasmodium falciparum and 174 (51.79%) cases by Plasmodium vivax. Malaria risk is the highest in the south of the settlement, associated with proximity to gold mining sites, intense land use, high levels of soil/vegetation humidity and low vegetation density.

CONCLUSIONS

Mid-resolution, remote sensing data and GIS-derived distance measures can be successfully combined with digital maps of the housing location of (non-) infected inhabitants to predict relative likelihood of disease infection through the analysis by logistic regression. Obtained findings on the relation between malaria cases and environmental factors should be applied in the future for land use planning in rural settlements in the Southern Amazon to minimize risks of disease transmission.

Further shrinking the malaria map: how can geospatial science help to achieve malaria elimination?

Malaria is one of the biggest contributors to deaths caused by infectious disease. More than 30 countries have planned or started programmes to target malaria elimination, often with explicit support from international donors. The spatial distribution of malaria, at all levels of endemicity, is heterogeneous. Moreover, populations living in low-endemic settings where elimination efforts might be targeted are often spatially heterogeneous. Geospatial methods, therefore, can help design, target, monitor, and assess malaria elimination programmes. Rapid advances in technology and analytical methods have allowed the spatial prediction of malaria risk and the development of spatial decision support systems, which can enhance elimination programmes by enabling accurate and timely resource allocation. However, no framework exists for assessment of geospatial instruments. Research is needed to identify measurable indicators of elimination progress and to quantify the effect of geospatial methods in achievement of elimination outcomes.

Efficiency of household reactive case detection for malaria in rural Southern Zambia: simulations based on cross-sectional surveys from two epidemiological settings

BACKGROUND

Case detection and treatment are critical to malaria control and elimination as infected individuals who do not seek medical care can serve as persistent reservoirs for transmission.

METHODS

Household malaria surveys were conducted in two study areas within Southern Province, Zambia in 2007 and 2008. Cross-sectional surveys were conducted approximately five times throughout the year in each of the two study areas. During study visits, adults and caretakers of children were administered a questionnaire and a blood sample was obtained for a rapid diagnostic test (RDT) for malaria. These data were used to estimate the proportions of individuals with malaria potentially identified through passive case detection at health care facilities and those potentially identified through reactive case finding. Simulations were performed to extrapolate data from sampled to non-sampled households. Radii of increasing size surrounding households with an index case were examined to determine the proportion of households with an infected individual that would be identified through reactive case detection.

RESULTS

In the 2007 high transmission setting, with a parasite prevalence of 23%, screening neighboring households within 500 meters of an index case could have identified 89% of all households with an RDT positive resident and 90% of all RDT positive individuals. In the 2008 low transmission setting, with a parasite prevalence of 8%, screening neighboring households within 500 meters of a household with an index case could have identified 77% of all households with an RDT positive resident and 76% of all RDT positive individuals.

CONCLUSIONS

Testing and treating individuals residing within a defined radius from an index case has the potential to be an effective strategy to identify and treat a large proportion of infected individuals who do not seek medical care, although the efficiency of this strategy is likely to decrease with declining parasite prevalence.

Risk factors associated with clinical malaria episodes in Bangladesh: a longitudinal study

Malaria is endemic to Bangladesh. In this longitudinal study, we used hydrologic, topographic, and socioeconomic risk factors to explain single and multiple malaria infections at individual and household levels. Malaria incidence was determined for 1,634 households in 54 villages in 2009 and 2010. During the entire study period 21.8% of households accounted for all (n = 497) malaria cases detected; 15.4% of households had 1 case and 6.4% had ≥ 2 cases. The greatest risk factors for malaria infection were low bed net ratio per household, house construction materials (wall), and high density of houses. Hydrologic and topographic factors were not significantly associated with malaria risk. This study identifies stable malaria hotspots and risk factors that should be considered for cost-effective targeting of malaria interventions that may contribute to potential elimination of malaria in Bangladesh.

Heterogeneity and changes in inequality of malaria risk after introduction of insecticide-treated bed nets in Macha, Zambia

In 2007, the first free mass distribution of insecticide-treated bed nets (ITNs) occurred in southern Zambia. To determine the effect of ITNs on heterogeneity in biting rates, human DNA from Anopheles arabiensis blood meals was genotyped to determine the number of hosts that had contributed to the blood meals. The multiple feeding rate decreased from 18.9% pre-ITN to 9.1% post-ITN, suggesting that mosquito biting had focused onto a smaller fraction of the population. Pre-ITN, 20% of persons in a household provided 40% of blood meals, which increased to 59% post-ITN. To measure heterogeneity over a larger scale, mosquitoes were collected in 90 households in two village areas. Of these households, 25% contributed 78.1% of An. arabiensis, and households with high frequencies of An. arabiensis were significantly spatially clustered. The results indicate that substantial heterogeneity in malaria risk exists at local and household levels, and household-level heterogeneity may be influenced by interventions, such as ITNs.

Topographic models for predicting malaria vector breeding habitats: potential tools for vector control managers

BACKGROUND

Identification of malaria vector breeding sites can enhance control activities. Although associations between malaria vector breeding sites and topography are well recognized, practical models that predict breeding sites from topographic information are lacking. We used topographic variables derived from remotely sensed Digital Elevation Models (DEMs) to model the breeding sites of malaria vectors. We further compared the predictive strength of two different DEMs and evaluated the predictability of various habitat types inhabited by Anopheles larvae.

METHODS

Using GIS techniques, topographic variables were extracted from two DEMs: 1) Shuttle Radar Topography Mission 3 (SRTM3, 90-m resolution) and 2) the Advanced Spaceborne Thermal Emission Reflection Radiometer Global DEM (ASTER, 30-m resolution). We used data on breeding sites from an extensive field survey conducted on an island in western Kenya in 2006. Topographic variables were extracted for 826 breeding sites and for 4520 negative points that were randomly assigned. Logistic regression modelling was applied to characterize topographic features of the malaria vector breeding sites and predict their locations. Model accuracy was evaluated using the area under the receiver operating characteristics curve (AUC).

RESULTS

All topographic variables derived from both DEMs were significantly correlated with breeding habitats except for the aspect of SRTM. The magnitude and direction of correlation for each variable were similar in the two DEMs. Multivariate models for SRTM and ASTER showed similar levels of fit indicated by Akaike information criterion (3959.3 and 3972.7, respectively), though the former was slightly better than the latter. The accuracy of prediction indicated by AUC was also similar in SRTM (0.758) and ASTER (0.755) in the training site. In the testing site, both SRTM and ASTER models showed higher AUC in the testing sites than in the training site (0.829 and 0.799, respectively). The predictability of habitat types varied. Drains, foot-prints, puddles and swamp habitat types were most predictable.

CONCLUSIONS

Both SRTM and ASTER models had similar predictive potentials, which were sufficiently accurate to predict vector habitats. The free availability of these DEMs suggests that topographic predictive models could be widely used by vector control managers in Africa to complement malaria control strategies.

Temporal and spatial patterns of serologic responses to Plasmodium falciparum antigens in a region of declining malaria transmission in southern Zambia

Background

Critical to sustaining progress in malaria control is comprehensive surveillance to identify outbreaks and prevent resurgence. Serologic responses to Plasmodium falciparum antigens can serve as a marker of recent transmission and serosurveillance may be feasible on a large scale.

Methods

Satellite images were used to construct a sampling frame for the random selection of households enrolled in prospective longitudinal and cross-sectional surveys in two study areas in Southern Province, Zambia, one in 2007 and the other in 2008 and 2009. Blood was collected and stored as dried spots from participating household members. A malaria rapid diagnostic test (RDT) was used to diagnose malaria. An enzyme immunoassay (EIA) was used to detect IgG antibodies to asexual stage P. falciparum whole parasite lysate using serum eluted from dried blood spots. The expected mean annual increase in optical density (OD) value for individuals with a documented prior history of recent malaria was determined using mixed models. SatScan was used to determine the spatial clustering of households with individuals with serological evidence of recent malaria, and these households were plotted on a malaria risk map.

Results

RDT positivity differed markedly between the study areas and years: 28% of participants for whom serologic data were available were RDT positive in the 2007 study area, compared to 8.1% and 1.4% in the 2008 and 2009 study area, respectively. Baseline antibody levels were measured in 234 participants between April and July 2007, 435 participants between February and December 2008, and 855 participants between January and December 2009. As expected, the proportion of seropositive individuals increased with age in each year. In a subset of participants followed longitudinally, RDT positivity at the prior visit was positively correlated with an increase in EIA OD values after adjusting for age in 2007 (0.261, p = 0.003) and in 2008 (0.116, p = 0.03). RDT positivity at the concurrent visit also was associated with an increase in EIA OD value in 2007 (mean increase 0.177, p = 0.002) but not in 2008 (−0.063, p =0.50). Households comprised of individuals with serologic evidence of recent malaria overlapped areas of high malaria risk for serologic data from 2009, when parasite prevalence was lowest.

Conclusions

Serological surveys to whole asexual P. falciparum antigens using blood collected as dried blood spots can be used to detect temporal and spatial patterns of malaria transmission in a region of declining malaria burden, and have the potential to identify focal areas of recent transmission.

Malaria research challenges in low prevalence settings

The prevalence of malaria has reduced significantly in some areas over the past decade. These reductions have made local elimination possible and the research agenda has shifted to this new priority. However, there are critical issues that arise when studying malaria in low transmission settings, particularly identifying asymptomatic infections, accurate detection of individuals with microparasitaemic infections, and achieving a sufficient sample size to have an adequately powered study. These challenges could adversely impact the study of malaria elimination if they remain unanswered.

Plasmodium vivax Duffy binding protein: baseline antibody responses and parasite polymorphisms in a well-consolidated settlement of the Amazon Region

OBJECTIVE

To investigate risk factors associated with the acquisition of antibodies against Plasmodium vivax Duffy binding protein (PvDBP) - a leading malaria vaccine candidate - in a well-consolidated agricultural settlement of the Brazilian Amazon Region and to determine the sequence diversity of the PvDBP ligand domain (DBP(II)) within the local malaria parasite population.

METHODS

Demographic, epidemiological and clinical data were collected from 541 volunteers using a structured questionnaire. Malaria parasites were detected by conventional microscopy and PCR, and blood collection was used for antibody assays and molecular characterisation of DBP(II).

RESULTS

The frequency of malaria infection was 7% (6% for P. vivax and 1% for P. falciparum), with malaria cases clustered near mosquito breeding sites. Nearly 50% of settlers had anti-PvDBP IgG antibodies, as detected by enzyme-linked immunosorbent assay (ELISA) with subject's age being the only strong predictor of seropositivity to PvDBP. Unexpectedly, low levels of DBP(II) diversity were found within the local malaria parasites, suggesting the existence of low gene flow between P. vivax populations, probably due to the relative isolation of the studied settlement.

CONCLUSION

The recognition of PvDBP by a significant proportion of the community, associated with low levels of DBP(II) diversity among local P. vivax, reinforces the variety of malaria transmission patterns in communities from frontier settlements. Such studies should provide baseline information for antimalarial vaccines now in development.

Near-present and future distribution of Anopheles albimanus in Mesoamerica and the Caribbean Basin modeled with climate and topographic data

BACKGROUND

Anopheles albimanus is among the most important vectors of human malaria in Mesoamerica and the Caribbean Basin (M-C). Here, we use topographic data and 1950-2000 climate (near present), and future climate (2080) layers obtained from general circulation models (GCMs) to project the probability of the species' presence, p(s), using the species distribution model MaxEnt.

RESULTS

The projected near-present distribution parameterized with 314 presence points related well to the known geographic distribution in the study region. Different model experiments suggest that the range of An. albimanus based on near-present climate surfaces covered at least 1.27 million km² in the M-C, although 2080 range was projected to decrease to 1.19 million km². Modeled p(s) was generally highest in Mesoamerica where many of the original specimens were collected. MaxEnt projected near-present maximum elevation at 1,937 m whereas 2080 maximum elevation was projected at 2,118 m. 2080 climate scenarios generally showed increased p(s) in Mesoamerica, although results varied for northern South America and no major range expansion into the mid-latitudes was projected by 2080.

CONCLUSIONS

MaxEnt experiments with near present and future climate data suggest that An. albimanus is likely to invade high-altitude (>2,000 m) areas by 2080 and therefore place many more people at risk of malaria in the M-C region even though latitudinal range expansion may be limited.

Reduced risk of malaria parasitemia following household screening and treatment: a cross-sectional and longitudinal cohort study

Background

In regions of declining malaria transmission, new strategies for control are needed to reduce transmission and achieve elimination. Artemisinin-combination therapy (ACT) is active against immature gametocytes and can reduce the risk of transmission. We sought to determine whether household screening and treatment of infected individuals provides protection against infection for household members.

Methodology/Principal Findings

The study was conducted in two areas in Southern Province, Zambia in 2007 and 2008/2009. To determine the impact of proactive case detection, households were randomly selected either to join a longitudinal cohort, in which participants were repeatedly screened throughout the year and those infected treated with artemether-lumefantrine, or a cross-sectional survey, in which participants were visited only once. Cross-sectional surveys were conducted throughout the year. The prevalence of RDT positivity was compared between the longitudinal and cross-sectional households at baseline and during follow-up using multilevel logistic regression. In the 2007 study area, 174 and 156 participants enrolled in the cross-sectional and longitudinal groups, respectively. In the 2008/2009 study area, 917 and 234 participants enrolled in the cross-sectional and longitudinal groups, respectively. In both study areas, participants and households in the longitudinal and cross-sectional groups were similar on demographic characteristics and prevalence of RDT positivity at baseline (2007: OR = 0.97; 95% CI:0.46, 2.03 | 2008/2009: OR = 1.28; 95% CI:0.44, 3.79). After baseline, the prevalence of RDT positivity was significantly lower in longitudinal compared to cross-sectional households in both study areas (2007: OR = 0.44; 95% CI:0.20, 0.96 | 2008/2009: OR = 0.16; 95% CI:0.05, 0.55).

Conclusions/Significance

Proactive case detection, consisting of screening household members with an RDT and treating those positive with ACT, can reduce transmission and provide indirect protection to household members. A targeted test and treat strategy could contribute to the elimination of malaria in regions of low transmission.

Changing individual-level risk factors for malaria with declining transmission in southern Zambia: a cross-sectional study

Background

Malaria elimination will require that both symptomatic- and asymptomatic-infected persons be identified and treated. However, well-characterized, individual-level risk factors for malaria may not be valid in regions with declining malaria transmission. Changes in individual-level correlates of malaria infection were evaluated over three years in a region of declining malaria transmission in southern Zambia.

Methods

Malaria surveys were conducted in two study areas within the catchment area of Macha Hospital, Zambia in 2007 and 2008/2009. A random sample of households was identified from a digitized satellite image of the study areas. Cross-sectional surveys were conducted approximately five times throughout the year in each of the two study areas. During study visits, adults and caretakers of children were administered questionnaires and a blood sample was obtained for a rapid diagnostic test (RDT) for malaria.

Results

In the 2007 study area, 330 individuals were surveyed. 40.9% of participants lived in a household with at least one insecticide-treated bed net (ITN); however, only 45.2% reported sleeping under the ITN. 23.9% of participants were RDT positive. Correlates of RDT positivity included younger age, the presence of symptoms, testing during the rainy season, using an open water source, and not sleeping under an ITN. In the 2008 study area, 435 individuals were surveyed. 77.0% of participants lived in a household with at least one ITN; however, only 56.4% reported sleeping under the ITN. 8.1% of participants were RDT positive. RDT positivity was negatively correlated with the presence of symptoms within the last two weeks but positively correlated with documented fever. In 2009, 716 individuals were surveyed in the same area as 2008. 63.7% of participants lived in a household with at least one ITN; however, only 57.7% reported sleeping under the ITN. 1.5% of participants were RDT positive. Only self-reported fever was significantly correlated with RDT positivity.

Conclusions

With declining malaria prevalence, few individual-level characteristics were correlated with RDT positivity. This lack of correlation with individual characteristics hampers identification of individuals infected with malaria. Strategies based on ecological or environmental risk factors may be needed to target control efforts and achieve further reductions and elimination.