Improving geographical accessibility modeling for operational use by local health actors.

BACKGROUND: Geographical accessibility to health facilities remains one of the main barriers to access care in rural areas of the developing world. Although methods and tools exist to model geographic accessibility, the lack of basic geographic information prevents their widespread use at the local level for targeted program implementation. The aim of this study was to develop very precise, context-specific estimates of geographic accessibility to care in a rural district of Madagascar to help with the design and implementation of interventions that improve access for remote populations. METHODS: We used a participatory approach to map all the paths, residential areas, buildings and rice fields on OpenStreetMap (OSM). We estimated shortest routes from every household in the District to the nearest primary health care center (PHC) and community health site (CHS) with the Open Source Routing Machine (OSMR) tool. Then, we used remote sensing methods to obtain a high resolution land cover map, a digital elevation model and rainfall data to model travel speed. Travel speed models were calibrated with field data obtained by GPS tracking in a sample of 168 walking routes. Model results were used to predict travel time to seek care at PHCs and CHSs for all the shortest routes estimated earlier. Finally, we integrated geographical accessibility results into an e-health platform developed with R Shiny. RESULTS: We mapped over 100,000 buildings, 23,000 km of footpaths, and 4925 residential areas throughout Ifanadiana district; these data are freely available on OSM. We found that over three quarters of the population lived more than one hour away from a PHC, and 10-15% lived more than 1 h away from a CHS. Moreover, we identified areas in the North and East of the district where the nearest PHC was further than 5 h away, and vulnerable populations across the district with poor geographical access (> 1 h) to both PHCs and CHSs. CONCLUSION: Our study demonstrates how to improve geographical accessibility modeling so that results can be context-specific and operationally actionable by local health actors. The importance of such approaches is paramount for achieving universal health coverage (UHC) in rural areas throughout the world.

Spatial and temporal dynamics of malaria in Madagascar.

BACKGROUND: Malaria is one of the primary health concerns in Madagascar. Based on the duration and intensity of transmission, Madagascar is divided into five epidemiological strata that range from low to mesoendemic transmission. In this study, the spatial and temporal dynamics of malaria within each epidemiological zone were studied. METHODS: The number of reported cases of uncomplicated malaria from 112 health districts between 2010 and 2014 were compiled and analysed. First, a Standardized Incidence Ratio was calculated to detect districts with anomalous incidence compared to the stratum-level incidence. Building on this, spatial and temporal malaria clusters were identified throughout the country and their variability across zones and over time was analysed. RESULTS: The incidence of malaria increased from 2010 to 2014 within each stratum. A basic analysis showed that districts with more than 50 cases per 1000 inhabitants are mainly located in two strata: East and West. Lower incidence values were found in the Highlands and Fringe zones. The standardization method revealed that the number of districts with a higher than expected numbers of cases increased through time and expanded into the Highlands and Fringe zones. The cluster analysis showed that for the endemic coastal region, clusters of districts migrated southward and the incidence of malaria was the highest between January and July with some variation within strata. CONCLUSION: This study identified critical districts with low incidence that shifted to high incidence and district that were consistent clusters across each year. The current study provided a detailed description of changes in malaria epidemiology and can aid the national malaria programme to reduce and prevent the expansion of the disease by targeting the appropriate areas.

Spatio-temporal dynamic of malaria in Ouagadougou, Burkina Faso, 2011-2015.

BACKGROUND: Given the scarcity of resources in developing countries, malaria treatment requires new strategies that target specific populations, time periods and geographical areas. While the spatial pattern of malaria transmission is known to vary depending on local conditions, its temporal evolution has yet to be evaluated. The aim of this study was to determine the spatio-temporal dynamic of malaria in the central region of Burkina Faso, taking into account meteorological factors. METHODS: Drawing on national databases, 101 health areas were studied from 2011 to 2015, together with weekly meteorological data (temperature, number of rain events, rainfall, humidity, wind speed). Meteorological factors were investigated using a principal component analysis (PCA) to reduce dimensions and avoid collinearities. The Box-Jenkins ARIMA model was used to test the stationarity of the time series. The impact of meteorological factors on malaria incidence was measured with a general additive model. A change-point analysis was performed to detect malaria transmission periods. For each transmission period, malaria incidence was mapped and hotspots were identified using spatial cluster detection. RESULTS: Malaria incidence never went below 13.7 cases/10,000 person-weeks. The first and second PCA components (constituted by rain/humidity and temperatures, respectively) were correlated with malaria incidence with a lag of 2 weeks. The impact of temperature was significantly non-linear: malaria incidence increased with temperature but declined sharply with high temperature. A significant positive linear trend was found for the entire time period. Three transmission periods were detected: low (16.8-29.9 cases/10,000 person-weeks), high (51.7-84.8 cases/10,000 person-weeks), and intermediate (26.7-32.2 cases/10,000 person-weeks). The location of clusters identified as high risk varied little across transmission periods. CONCLUSION: This study highlighted the spatial variability and relative temporal stability of malaria incidence around the capital Ouagadougou, in the central region of Burkina Faso. Despite increasing efforts in fighting the disease, malaria incidence remained high and increased over the period of study. Hotspots, particularly those detected for low transmission periods, should be investigated further to uncover the local environmental and behavioural factors of transmission, and hence to allow for the development of better targeted control strategies.

Analysing trends and forecasting malaria epidemics in Madagascar using a sentinel surveillance network: a web-based application.

BACKGROUND: The use of a malaria early warning system (MEWS) to trigger prompt public health interventions is a key step in adding value to the epidemiological data routinely collected by sentinel surveillance systems. METHODS: This study describes a system using various epidemic thresholds and a forecasting component with the support of new technologies to improve the performance of a sentinel MEWS. Malaria-related data from 21 sentinel sites collected by Short Message Service are automatically analysed to detect malaria trends and malaria outbreak alerts with automated feedback reports. RESULTS: Roll Back Malaria partners can, through a user-friendly web-based tool, visualize potential outbreaks and generate a forecasting model. The system already demonstrated its ability to detect malaria outbreaks in Madagascar in 2014. CONCLUSION: This approach aims to maximize the usefulness of a sentinel surveillance system to predict and detect epidemics in limited-resource environments.

Habitat fragmentation alters the properties of a host-parasite network: rodents and their helminths in South-East Asia.

1. While the effects of deforestation and habitat fragmentation on parasite prevalence or richness are well investigated, host-parasite networks are still understudied despite their importance in understanding the mechanisms of these major disturbances. Because fragmentation may negatively impact species occupancy, abundance and co-occurrence, we predict a link between spatiotemporal changes in habitat and the architecture of host-parasite networks. 2. For this, we used an extensive data set on 16 rodent species and 29 helminth species from seven localities of South-East Asia. We analysed the effects of rapid deforestation on connectance and modularity of helminth-parasite networks. We estimated both the degree of fragmentation and the rate of deforestation through the development of land uses and their changes through the last 20 to 30 years in order to take into account the dynamics of habitat fragmentation in our statistical analyses. 3. We found that rapid fragmentation does not affect helminth species richness per se but impacts host-parasite interactions as the rodent-helminth network becomes less connected and more modular. 4. Our results suggest that parasite sharing among host species may become more difficult to maintain with the increase of habitat disturbance.

Climate-driven models of leptospirosis dynamics in tropical islands from three oceanic basins.

BACKGROUND: Leptospirosis is a neglected zoonosis which remains poorly known despite its epidemic potential, especially in tropical islands where outdoor lifestyle, vulnerability to invasive reservoir species and hot and rainy climate constitute higher risks for infections. Burden remains poorly documented while outbreaks can easily overflow health systems of these isolated and poorly populated areas. Identification of generic patterns driving leptospirosis dynamics across tropical islands would help understand its epidemiology for better preparedness of communities. In this study, we aim to model leptospirosis seasonality and outbreaks in tropical islands based on precipitation and temperature indicators. METHODOLOGY/PRINCIPAL FINDINGS: We adjusted machine learning models on leptospirosis surveillance data from seven tropical islands (Guadeloupe, Reunion Island, Fiji, Futuna, New Caledonia, and Tahiti) to investigate 1) the effect of climate on the disease's seasonal dynamic, i.e., the centered seasonal profile and 2) inter-annual anomalies, i.e., the incidence deviations from the seasonal profile. The model was then used to estimate seasonal dynamics of leptospirosis in Vanuatu and Puerto Rico where disease incidence data were not available. A robust model, validated across different islands with leave-island-out cross-validation and based on current and 2-month lagged precipitation and current and 1-month lagged temperature, can be constructed to estimate the seasonal dynamic of leptospirosis. In opposition, climate determinants and their importance in estimating inter-annual anomalies highly differed across islands. CONCLUSIONS/SIGNIFICANCE: Climate appears as a strong determinant of leptospirosis seasonality in tropical islands regardless of the diversity of the considered environments and the different lifestyles across the islands. However, predictive and expandable abilities from climate indicators weaken when estimating inter-annual outbreaks and emphasize the importance of these local characteristics in the occurrence of outbreaks.

Challenges for ticks and tick-borne diseases research in Southeast Asia: Insight from the first international symposium in Cambodia.

BACKGROUND: Ticks, as critical vectors of a variety of pathogens, pose a significant public health challenge globally. In Southeast Asia (SEA), ticks are responsible for transmitting a diverse array of pathogens affecting humans and animals. The geographical and ecological diversity of SEA provides a unique environment that supports a wide range of tick species, which complicates the management and study of tick-borne diseases (TBDs). METHODOLOGY/PRINCIPAL FINDINGS: This article synthesizes findings from the first international symposium on ticks and TBDs in Southeast Asia, held in Phnom Penh on June 22 and 23, 2023. It highlights regional efforts to understand tick ecology and pathogen transmission. This paper proposes to present a summary of the various presentations given during the symposium following 3 main parts. The first one is devoted to the state of knowledge regarding ticks and TBDs in SEA countries, with presentations from 6 different countries, namely Cambodia, Indonesia, Laos, Malaysia, Thailand, and Vietnam. The second part focuses on the development of new research approaches on tick-borne pathogens (TBPs) and TBDs. The last part is a summary of the round table discussion held on the final day, with the aim of defining the most important challenges and recommendations for researches on TBP and TBD in the SEA region. CONCLUSIONS/SIGNIFICANCE: Key topics discussed include advancements in diagnostic tools, such as MALDI-TOF MS and proteomics, and the development of sustainable strategies for tick management and disease prevention. The symposium facilitated the exchange of knowledge and collaborative networks among experts from various disciplines, promoting a unified approach to tackling TBDs in the region. The symposium underscored the need for enhanced surveillance, diagnostics, and inter-regional cooperation to manage the threat of TBDs effectively. Recommendations include the establishment of a regional database for tick identification and the expansion of vector competence studies. These initiatives are crucial for developing targeted interventions and understanding the broader implications of climate change and urbanization on the prevalence of TBDs.

Cytonuclear discordance among Southeast Asian black rats (Rattus rattus complex).

Black rats are major invasive vertebrate pests with severe ecological, economic and health impacts. Remarkably, their evolutionary history has received little attention, and there is no firm agreement on how many species should be recognized within the black rat complex. This species complex is native to India and Southeast Asia. According to current taxonomic classification, there are three taxa living in sympatry in several parts of Thailand, Cambodia and Lao People's Democratic Republic, where this study was conducted: two accepted species (Rattus tanezumi, Rattus sakeratensis) and an additional mitochondrial lineage of unclear taxonomic status referred to here as 'Rattus R3'. We used extensive sampling, morphological data and diverse genetic markers differing in rates of evolution and parental inheritance (two mitochondrial DNA genes, one nuclear gene and eight microsatellite loci) to assess the reproductive isolation of these three taxa. Two close Asian relatives, Rattus argentiventer and Rattus exulans, were also included in the genetic analyses. Genetic analyses revealed discordance between the mitochondrial and nuclear data. Mitochondrial phylogeny studies identified three reciprocally monophyletic clades in the black rat complex. However, studies of the phylogeny of the nuclear exon interphotoreceptor retinoid-binding protein gene and clustering and assignation analyses with eight microsatellites failed to separate R. tanezumi and R3. Morphometric analyses were consistent with nuclear data. The incongruence between mitochondrial and nuclear (and morphological) data rendered R. tanezumi/R3 paraphyletic for mitochondrial lineages with respect to R. sakeratensis. Various evolutionary processes, such as shared ancestral polymorphism and incomplete lineage sorting or hybridization with massive mitochondrial introgression between species, may account for this unusual genetic pattern in mammals.

Is Leopoldamys neilli (Rodentia, Muridae) a synonym of Leopoldamys herberti? A reply to Balakirev et al. (2013).

Recently, Balakirev et al. (2013) presented a taxonomic revision of the genus Leopoldamys based on phylogenetic analyses. They identified five main Leopoldamys genetic lineages and suggested to rename several of them. According to these authors, the genetic lineage previously thought to belong to L. edwardsi (lineage L1) should be assigned to L. revertens while L. neilli (lineage L2) should be considered as a junior synonym of L. herberti. Using molecular and morphological data from a large sampling of Leopoldamys specimens, the aim of the present study was to investigate the taxonomic status of L. herberti and L. neilli. This study reveals that, contrary to Balakirev et al.'s statement, both genetic lineages L1 and L2 occur in Nakhon Ratchasima Province, close to the type locality of L. herberti. We also show that the external measurements and color pattern of L. herberti are highly similar to those of L1 specimens but are not consistent with the morphology of L2 specimens. Therefore these results strongly suggest that L. herberti should be assigned to the genetic lineage L1. Consequently L. neilli should not be considered as a junior synonym of L. herberti and this study confirms that the appropriate name of the genetic lineage L2 is L. neilli. Moreover, as our results show that L. herberti should be assigned to the lineage L1, this name has nomenclatural priority over L. revertens, the species name suggested by Balakirev et al. (2013) for this lineage.

Malaria temporal dynamic clustering for surveillance and intervention planning.

BACKGROUND: Targeting interventions where most needed and effective is crucial for public health. Malaria control and elimination strategies increasingly rely on stratification to guide surveillance, to allocate vector control campaigns, and to prioritize access to community-based early diagnosis and treatment (EDT). We developed an original approach of dynamic clustering to improve local discrimination between heterogeneous malaria transmission settings. METHODS: We analysed weekly malaria incidence records obtained from community-based EDT (malaria posts) in Karen/Kayin state, Myanmar. We smoothed longitudinal incidence series over multiple seasons using functional transformation. We regrouped village incidence series into clusters using a dynamic time warping clustering and compared them to the standard, 5-category annual incidence standard stratification. RESULTS: We included 1115 villages from 2016 to 2020. We identified eleven P. falciparum and P. vivax incidence clusters which differed by amplitude, trends and seasonality. Specifically the 124 villages classified as "high transmission area" in the standard P. falciparum stratification belonged to the 11 distinct groups when accounting to inter-annual trends and intra-annual variations. Likewise for P. vivax, 399 "high transmission" villages actually corresponded to the 11 distinct dynamics. CONCLUSION: Our temporal dynamic clustering methodology is easy to implement and extracts more information than standard malaria stratification. Our method exploits longitudinal surveillance data to distinguish local dynamics, such as increasing inter-annual trends or seasonal differences, providing key information for decision-making. It is relevant to malaria strategies in other settings and to other diseases, especially when many countries deploy health information systems and collect increasing amounts of health outcome data. FUNDING: The Bill & Melinda Gates Foundation, The Global Fund against AIDS, Tuberculosis and Malaria (the Regional Artemisinin Initiative) and the Wellcome Trust funded the METF program.

'Forest malaria' in Myanmar? Tracking transmission landscapes in a diversity of environments.

BACKGROUND: In the Greater Mekong Subregion, case-control studies and national-level analyses have shown an association between malaria transmission and forest activities. The term 'forest malaria' hides the diversity of ecosystems in the GMS, which likely do not share a uniform malaria risk. To reach malaria elimination goals, it is crucial to document accurately (both spatially and temporally) the influence of environmental factors on malaria to improve resource allocation and policy planning within given areas. The aim of this ecological study is to characterize the association between malaria dynamics and detailed ecological environments determined at village level over a period of several years in Kayin State, Myanmar. METHODS: We characterized malaria incidence profiles at village scale based on intra- and inter-annual variations in amplitude, seasonality, and trend over 4 years (2016-2020). Environment was described independently of village localization by overlaying a 2-km hexagonal grid over the region. Specifically, hierarchical classification on principal components, using remote sensing data of high spatial resolution, was used to assign a landscape and a climate type to each grid cell. We used conditional inference trees and random forests to study the association between the malaria incidence profile of each village, climate and landscape. Finally, we constructed eco-epidemiological zones to stratify and map malaria risk in the region by summarizing incidence and environment association information. RESULTS: We identified a high diversity of landscapes (n = 19) corresponding to a gradient from pristine to highly anthropogenically modified landscapes. Within this diversity of landscapes, only three were associated with malaria-affected profiles. These landscapes were composed of a mosaic of dense and sparse forest fragmented by small agricultural patches. A single climate with moderate rainfall and a temperature range suitable for mosquito presence was also associated with malaria-affected profiles. Based on these environmental associations, we identified three eco-epidemiological zones marked by later persistence of Plasmodium falciparum, high Plasmodium vivax incidence after 2018, or a seasonality pattern in the rainy season. CONCLUSIONS: The term forest malaria covers a multitude of contexts of malaria persistence, dynamics and populations at risk. Intervention planning and surveillance could benefit from consideration of the diversity of landscapes to focus on those specifically associated with malaria transmission.

Diversity of gastrointestinal helminths among murid rodents from northern and northeastern Thailand.

The presence of gastrointestinal helminths (GI helminths) was investigated among 725 murid rodents, trapped in various habitats of Nan, Loei and Buri Ram Provinces, Thailand. The study revealed 17 species of rodents infected with 21 species or taxonomic groups of parasites (3 trematodes, 3 cestodes, 14 nematodes and 1 acanthocephalan). The overall prevalence of infection was 57.7% (418/725). Of the gastrointestinal (GI) helminths, the dominant parasitic group was members of the family Trichostrongylidae (24.3%), followed by the cestodes Raillietina sp (17.1%) and Hymenolepis diminuta (8.6%) and the nematode Syphacia muris (8.6%). The GI helminthic infection rates were highest in Mus caroli (81.8%), Mus cervicolor (76.5%), Leopoldamys edwardsi (75.0%), Bandicota indica (71.5%) and Bandicota savilei (71.4%). Highest rodent species richness (RSR) and helminth species richness (HSR) rates were found in Loei, followed by Nan and Buri Ram. The helminth prevalence rate was higher in rodents from Nan, followed by rodents from Loei and Buri Ram. Rodents from irrigated fields had the highest infection rates followed by rodents from upland or dry agricultural areas, forests and domestic habitats. Raillietina sp, Rodentolepis nana (syn. Hymenolepis nana), Hymenolepis diminuta, Moniliformis moniliformis and Cyclodontostomum purvisi, considered zoonotic parasites, were mainly found in rodents from domestic habitats and lowland irrigated fields.

Unraveling the invisible leptospirosis in mainland Southeast Asia and its fate under climate change.

Leptospirosis is a neglected waterborne zoonosis of growing concern in tropical and low-income regions. Endemic in Southeast Asia, its distribution and environmental factors such as climate controlling its dynamics remain poorly documented. In this paper, we investigate for the first time the current and future leptospirosis burden at a local scale in mainland Southeast Asia. We adjusted machine-learning models on incidence reports from the Thai surveillance system to identify environmental determinants of leptospirosis. The explanatory variables tested in our models included climate, topographic, land cover and soil variables. The model performing the best in cross-validation was used to estimate the current incidence regionally in Thailand, Myanmar, Cambodia, Vietnam and Laos. It then allowed to predict the spatial distribution of leptospirosis future burden from 2021 to 2100 based on an ensemble of CMIP6 climate model projections and 4 Shared Socio-economics Pathways ranging from the most optimistic to the no-climate policy outcomes (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5). Leptospirosis incidence was best estimated by 10 environmental variables: four landscape-, four rainfall-, two temperature-related variables. Of all tested scenario, the worst-case scenario of climate change (SSP5-8.5) surprisingly appeared as the best-case scenario for the future of leptospirosis since it would induce a significant global decline in disease incidence in Southeast Asia mainly driven by the increasing temperatures. These global patterns are however contrasted regionally with some regions showing increased incidence in the future. Our work highlights climate and the environment as major drivers of leptospirosis incidence in Southeast Asia. Applying our model to regions where leptospirosis is not routinely monitored suggests an overlooked burden in the region. As our model focuses on leptospirosis responses to environmental drivers only, some other factors, such as poverty, lifestyle or behavioral changes, could further influence these estimated future patterns.

Predicting the Effects of Climate Change on Dengue Vector Densities in Southeast Asia through Process-Based Modeling.

BACKGROUND: Aedes aegypti and Ae. albopictus mosquitoes are major vectors for several human diseases of global importance, such as dengue and yellow fever. Their life cycles and hosted arboviruses are climate sensitive and thus expected to be impacted by climate change. Most studies investigating climate change impacts on Aedes at global or continental scales focused on their future global distribution changes, whereas a single study focused on its effects on Ae. aegypti densities regionally. OBJECTIVES: A process-based approach was used to model densities of Ae. aegypti and Ae. albopictus and their potential evolution with climate change using a panel of nine CMIP6 climate models and climate scenarios ranging from strong to low mitigation measures at the Southeast Asian scale and for the next 80 y. METHODS: The process-based model described, through a system of ordinary differential equations, the variations of mosquito densities in 10 compartments, corresponding to 10 different stages of mosquito life cycle, in response to temperature and precipitation variations. Local field data were used to validate model outputs. RESULTS: We show that both species densities will globally increase due to future temperature increases. In Southeast Asia by the end of the century, Ae. aegypti densities are expected to increase from 25% with climate mitigation measures to 46% without; Ae. albopictus densities are expected to increase from 13%-21%, respectively. However, we find spatially contrasted responses at the seasonal scales with a significant decrease in Ae. albopictus densities in lowlands during summer in the future. DISCUSSION: These results contrast with previous results, which brings new insight on the future impacts of climate change on Aedes densities. Major sources of uncertainties, such as mosquito model parametrization and climate model uncertainties, were addressed to explore the limits of such modeling. https://doi.org/10.1289/EHP11068.

Determining the spatial distribution of environmental and socio-economic suitability for human leptospirosis in the face of limited epidemiological data.

BACKGROUND: Leptospirosis is among the leading zoonotic causes of morbidity and mortality worldwide. Knowledge about spatial patterns of diseases and their underlying processes have the potential to guide intervention efforts. However, leptospirosis is often an underreported and misdiagnosed disease and consequently, spatial patterns of the disease remain unclear. In the absence of accurate epidemiological data in the urban agglomeration of Santa Fe, we used a knowledge-based index and cluster analysis to identify spatial patterns of environmental and socioeconomic suitability for the disease and potential underlying processes that shape them. METHODS: We geocoded human leptospirosis cases derived from the Argentinian surveillance system during the period 2010 to 2019. Environmental and socioeconomic databases were obtained from satellite images and publicly available platforms on the web. Two sets of human leptospirosis determinants were considered according to the level of their support by the literature and expert knowledge. We used the Zonation algorithm to build a knowledge-based index and a clustering approach to identify distinct potential sets of determinants. Spatial similarity and correlations between index, clusters, and incidence rates were evaluated. RESULTS: We were able to geocode 56.36% of the human leptospirosis cases reported in the national epidemiological database. The knowledge-based index showed the suitability for human leptospirosis in the UA Santa Fe increased from downtown areas of the largest cities towards peri-urban and suburban areas. Cluster analysis revealed downtown areas were characterized by higher levels of socioeconomic conditions. Peri-urban and suburban areas encompassed two clusters which differed in terms of environmental determinants. The highest incidence rates overlapped areas with the highest suitability scores, the strength of association was low though (CSc r = 0.21, P < 0.001 and ESc r = 0.19, P < 0.001). CONCLUSIONS: We present a method to analyze the environmental and socioeconomic suitability for human leptospirosis based on literature and expert knowledge. The methodology can be thought as an evolutive and perfectible scheme as more studies are performed in the area and novel information regarding determinants of the disease become available. Our approach can be a valuable tool for decision-makers since it can serve as a baseline to plan intervention measures.

Outdoor residual spraying for malaria vector-control in Kayin (Karen) state, Myanmar: A cluster randomized controlled trial.

Outdoor and early biting by mosquitoes challenge the efficacy of bed nets and indoor residual spraying against malaria in the Greater Mekong Subregion. The objective of this study was to assess the efficacy of outdoor residual spraying (ORS) for malaria vector-control in this region. A cluster randomized controlled trial was conducted between July 2018 and April 2019 in twelve villages in Karen (Kayin) state, Myanmar. Villages were randomly assigned to receive either a single round of ORS with a capsule suspension of lambda-cyhalothrin for two days in October or no intervention (six villages per group). The primary endpoint was the biting rate of malaria mosquitoes assessed with human-landing catch and cow-baited trap collection methods, and was analyzed with a Bayesian multi-level model. In the intervention villages, the proportion of households located within the sprayed area ranged between 42 and 100% and the application rate ranged between 63 and 559 g of active ingredient per hectare. At baseline, the median of Anopheles biting rate estimates in the twelve villages was 2 bites per person per night (inter-quartile range [IQR] 0-5, range 0-48) indoors, 6 bites per person per night (IQR 2-16, range 0-342) outdoors and 206 bites per cow per night (IQR 83-380, range 19-1149) in the cow-baited trap. In intention-to-treat analysis, it was estimated that ORS reduced biting rate by 72% (95% confidence interval [CI] 63-79) from Month 0 to Month 3 and by 79% (95% CI 62-88) from Month 4 to Month 6, considering control villages as the reference. In conclusion, ORS rapidly reduces the biting rates of malaria mosquitoes in a Southeast Asian setting where the vectors bite mostly outdoors and at a time when people are not protected by mosquito bed nets.

Malaria in Cambodia: A Retrospective Analysis of a Changing Epidemiology 2006-2019.

BACKGROUND: In Cambodia, malaria persists with changing epidemiology and resistance to antimalarials. This study aimed to describe how malaria has evolved spatially from 2006 to 2019 in Cambodia. METHODS: We undertook a secondary analysis of existing malaria data from all government healthcare facilities in Cambodia. The epidemiology of malaria was described by sex, age, seasonality, and species. Spatial clusters at the district level were identified with a Poisson model. RESULTS: Overall, incidence decreased from 7.4 cases/1000 population in 2006 to 1.9 in 2019. The decrease has been drastic for females, from 6.7 to 0.6/1000. Adults aged 15-49 years had the highest malaria incidence among all age groups. The proportion of Plasmodium (P.) falciparum + Mixed among confirmed cases declined from 87.9% (n = 67,489) in 2006 to 16.6% (n = 5290) in 2019. Clusters of P. falciparum + Mixed and P. vivax + Mixed were detected in forested provinces along all national borders. CONCLUSIONS: There has been a noted decrease in P. falciparum cases in 2019, suggesting that an intensification plan should be maintained. A decline in P. vivax cases was also noted, although less pronounced. Interventions aimed at preventing new infections of P. vivax and relapses should be prioritized. All detected malaria cases should be captured by the national surveillance system to avoid misleading trends.

Geographic barriers to achieving universal health coverage: evidence from rural Madagascar.

Poor geographic access can persist even when affordable and well-functioning health systems are in place, limiting efforts for universal health coverage (UHC). It is unclear how to balance support for health facilities and community health workers in UHC national strategies. The goal of this study was to evaluate how a health system strengthening (HSS) intervention aimed towards UHC affected the geographic access to primary care in a rural district of Madagascar. For this, we collected the fokontany of residence (lowest administrative unit) from nearly 300 000 outpatient consultations occurring in facilities of Ifanadiana district in 2014-2017 and in the subset of community sites supported by the HSS intervention. Distance from patients to facilities was accurately estimated following a full mapping of the district's footpaths and residential areas. We modelled per capita utilization for each fokontany through interrupted time-series analyses with control groups, accounting for non-linear relationships with distance and travel time among other factors, and we predicted facility utilization across the district under a scenario with and without HSS. Finally, we compared geographic trends in primary care when combining utilization at health facilities and community sites. We find that facility-based interventions similar to those in UHC strategies achieved high utilization rates of 1-3 consultations per person year only among populations living in close proximity to facilities. We predict that scaling only facility-based HSS programmes would result in large gaps in access, with over 75% of the population unable to reach one consultation per person year. Community health delivery, available only for children under 5 years, provided major improvements in service utilization regardless of their distance from facilities, contributing to 90% of primary care consultations in remote populations. Our results reveal the geographic limits of current UHC strategies and highlight the need to invest on professionalized community health programmes with larger scopes of service.

Geographic barriers to establishing a successful hospital referral system in rural Madagascar.

BACKGROUND: The provision of emergency and hospital care has become an integral part of the global vision for universal health coverage. To strengthen secondary care systems, we need to accurately understand the time necessary for populations to reach a hospital. The goal of this study was to develop methods that accurately estimate referral and prehospital time for rural districts in low and middle-income countries. We used these estimates to assess how local geography can limit the impact of a strengthened referral programme in a rural district of Madagascar. METHODS: We developed a database containing: travel speed by foot and motorised vehicles in Ifanadiana district; a full mapping of all roads, footpaths and households; and remotely sensed data on terrain, land cover and climatic characteristics. We used this information to calibrate estimates of referral and prehospital time based on the shortest route algorithms and statistical models of local travel speed. We predict the impact on referral numbers of strategies aimed at reducing referral time for underserved populations via generalised linear mixed models. RESULTS: About 10% of the population lived less than 2 hours from the hospital, and more than half lived over 4 hours away, with variable access depending on climatic conditions. Only the four health centres located near the paved road had referral times to the hospital within 1 hour. Referral time remained the main barrier limiting the number of referrals despite health system strengthening efforts. The addition of two new referral centres is estimated to triple the population living within 2 hours from a centre with better emergency care capacity and nearly double the number of expected referrals. CONCLUSION: This study demonstrates how adapting geographic accessibility modelling methods to local scales can occur through improving the precision of travel time estimates and pairing them with data on health facility use.

Revisiting the taxonomy of the Rattini tribe: a phylogeny-based delimitation of species boundaries.

BACKGROUND: Rodents are recognized as hosts for at least 60 zoonotic diseases and may represent a serious threat for human health. In the context of global environmental changes and increasing mobility of humans and animals, contacts between pathogens and potential animal hosts and vectors are modified, amplifying the risk of disease emergence. An accurate identification of each rodent at a specific level is needed in order to understand their implications in the transmission of diseases. Among the Muridae, the Rattini tribe encompasses 167 species inhabiting South East Asia, a hotspot of both biodiversity and emerging and re-emerging diseases. The region faces growing economical development that affects habitats, biodiversity and health. Rat species have been demonstrated as significant hosts of pathogens but are still difficult to recognize at a specific level using morphological criteria. DNA-barcoding methods appear as accurate tools for rat species identification but their use is hampered by the need of reliable identification of reference specimens. In this study, we explore and highlight the limits of the current taxonomy of the Rattini tribe. RESULTS: We used the DNA sequence information itself as the primary information source to establish group membership and estimate putative species boundaries. We sequenced two mitochondrial and one nuclear genes from 122 rat samples to perform phylogenetic reconstructions. The method of Pons and colleagues (2006) that determines, with no prior expectations, the locations of ancestral nodes defining putative species was then applied to our dataset. To give an appropriate name to each cluster recognized as a putative species, we reviewed information from the literature and obtained sequences from a museum holotype specimen following the ancient DNA criteria. CONCLUSIONS: Using a recently developed methodology, this study succeeds in refining the taxonomy of one of the most difficult groups of mammals. Most of the species expected within the area were retrieved but new putative species limits were also indicated, in particular within Berylmys and Rattus genera, where future taxonomic studies should be directed. Our study lays the foundations to better investigate rodent-born diseases in South East Asia and illustrates the relevance of evolutionary studies for health and medical sciences.