Expanding community case management of malaria to all ages can improve universal access to malaria diagnosis and treatment: results from a cluster randomized trial in Madagascar.

BACKGROUND: Global progress on malaria control has stalled recently, partly due to challenges in universal access to malaria diagnosis and treatment. Community health workers (CHWs) can play a key role in improving access to malaria care for children under 5 years (CU5), but national policies rarely permit them to treat older individuals. We conducted a two-arm cluster randomized trial in rural Madagascar to assess the impact of expanding malaria community case management (mCCM) to all ages on health care access and use. METHODS: Thirty health centers and their associated CHWs in Farafangana District were randomized 1:1 to mCCM for all ages (intervention) or mCCM for CU5 only (control). Both arms were supported with CHW trainings on malaria case management, community sensitization on free malaria care, monthly supervision of CHWs, and reinforcement of the malaria supply chain. Cross-sectional household surveys in approximately 1600 households were conducted at baseline (Nov-Dec 2019) and endline (Nov-Dec 2021). Monthly data were collected from health center and CHW registers for 36 months (2019-2021). Intervention impact was assessed via difference-in-differences analyses for survey data and interrupted time-series analyses for health system data. RESULTS: Rates of care-seeking for fever and malaria diagnosis nearly tripled in both arms (from less than 25% to over 60%), driven mostly by increases in CHW care. Age-expanded mCCM yielded additional improvements for individuals over 5 years in the intervention arm (rate ratio for RDTs done in 6-13-year-olds, RRRDT6-13 years = 1.65; 95% CIs 1.45-1.87), but increases were significant only in health system data analyses. Age-expanded mCCM was associated with larger increases for populations living further from health centers (RRRDT6-13 years = 1.21 per km; 95% CIs 1.19-1.23). CONCLUSIONS: Expanding mCCM to all ages can improve universal access to malaria diagnosis and treatment. In addition, strengthening supply chain systems can achieve significant improvements even in the absence of age-expanded mCCM. TRIAL REGISTRATION: The trial was registered at the Pan-African Clinical Trials Registry (#PACTR202001907367187).

Heterogeneity in elimination efforts could increase the risk of resurgence of lymphatic filariasis in Madagascar.

BACKGROUND: Progress in lymphatic filariasis (LF) elimination is spatially heterogeneous in many endemic countries, which may lead to resurgence in areas that have achieved elimination. Understanding the drivers and consequences of such heterogeneity could help inform strategies to reach global LF elimination goals by 2030. This study assesses whether differences in age-specific compliance with mass drug administration (MDA) could explain LF prevalence patterns in southeastern Madagascar and explores how spatial heterogeneity in prevalence and age-specific MDA compliance may affect the risk of LF resurgence after transmission interruption. METHODOLOGY: We used LYMFASIM model with parameters in line with the context of southeastern Madagascar and explored a wide range of scenarios with different MDA compliance for adults and children (40-100%) to estimate the proportion of elimination, non-elimination and resurgence events associated with each scenario. Finally, we evaluated the risk of resurgence associated with different levels of migration (2-6%) from surrounding districts combined with varying levels of LF microfilaria (mf) prevalence (0-24%) during that same study period. RESULTS: Differences in MDA compliance between adults and children better explained the observed heterogeneity in LF prevalence for these age groups than differences in exposure alone. The risk of resurgence associated with differences in MDA compliance scenarios ranged from 0 to 19% and was highest when compliance was high for children (e.g. 90%) and low for adults (e.g. 50%). The risk of resurgence associated with migration was generally higher, exceeding 60% risk for all the migration levels explored (2-6% per year) when mf prevalence in the source districts was between 9% and 20%. CONCLUSION: Gaps in the implementation of LF elimination programme can increase the risk of resurgence and undermine elimination efforts. In Madagascar, districts that have not attained elimination pose a significant risk for those that have achieved it. More research is needed to help guide LF elimination programme on the optimal strategies for surveillance and control that maximize the chances to sustain elimination and avoid resurgence.

Evaluation of a novel approach to community health care delivery in Ifanadiana District, Madagascar.

Despite widespread adoption of community health (CH) systems, there are evidence gaps to support global best practice in remote settings where access to health care is limited and community health workers (CHWs) may be the only available providers. The nongovernmental health organization Pivot partnered with the Ministry of Public Health (MoPH) to pilot a new enhanced community health (ECH) model in rural Madagascar, where one CHW provided care at a stationary CH site while additional CHWs provided care via proactive household visits. The program included professionalization of the CHW workforce (i.e., targeted recruitment, extended training, financial compensation) and twice monthly supervision of CHWs. For the first eighteen months of implementation (October 2019-March 2021), we compared utilization and proxy measures of quality of care in the intervention commune (local administrative unit) and five comparison communes with strengthened community health programs under a different model. This allowed for a quasi-experimental study design of the impact of ECH on health outcomes using routinely collected programmatic data. Despite the substantial support provided to other CHWs, the results show statistically significant improvements in nearly every indicator. Sick child visits increased by more than 269.0% in the intervention following ECH implementation. Average per capita monthly under-five visits were 0.25 in the intervention commune and 0.19 in the comparison communes (p<0.01). In the intervention commune, 40.3% of visits were completed at the household via proactive care. CHWs completed all steps of the iCCM protocol in 85.4% of observed visits in the intervention commune (vs 57.7% in the comparison communes, p-value<0.01). This evaluation demonstrates that ECH can improve care access and the quality of service delivery in a rural health district. Further research is needed to assess the generalizability of results and the feasibility of national scale-up as the MoPH continues to define the national community health program.

Applying a zero-corrected, gravity model estimator reduces bias due to heterogeneity in healthcare utilization in community-scale, passive surveillance datasets of endemic diseases.

Data on population health are vital to evidence-based decision making but are rarely adequately localized or updated in continuous time. They also suffer from low ascertainment rates, particularly in rural areas where barriers to healthcare can cause infrequent touch points with the health system. Here, we demonstrate a novel statistical method to estimate the incidence of endemic diseases at the community level from passive surveillance data collected at primary health centers. The zero-corrected, gravity-model (ZERO-G) estimator explicitly models sampling intensity as a function of health facility characteristics and statistically accounts for extremely low rates of ascertainment. The result is a standardized, real-time estimate of disease incidence at a spatial resolution nearly ten times finer than typically reported by facility-based passive surveillance systems. We assessed the robustness of this method by applying it to a case study of field-collected malaria incidence rates from a rural health district in southeastern Madagascar. The ZERO-G estimator decreased geographic and financial bias in the dataset by over 90% and doubled the agreement rate between spatial patterns in malaria incidence and incidence estimates derived from prevalence surveys. The ZERO-G estimator is a promising method for adjusting passive surveillance data of common, endemic diseases, increasing the availability of continuously updated, high quality surveillance datasets at the community scale.

Morbidity and mortality burden of COVID-19 in rural Madagascar: results from a longitudinal cohort and nested seroprevalence study.

INTRODUCTION: Three years into the pandemic, there remains significant uncertainty about the true infection and mortality burden of COVID-19 in the World Health Organization Africa region. High quality, population-representative studies in Africa are rare and tend to be conducted in national capitals or large cities, leaving a substantial gap in our understanding of the impact of COVID-19 in rural, low-resource settings. Here, we estimated the spatio-temporal morbidity and mortality burden associated with COVID-19 in a rural health district of Madagascar until the first half of 2021. METHODS: We integrated a nested seroprevalence study within a pre-existing longitudinal cohort conducted in a representative sample of 1600 households in Ifanadiana District, Madagascar. Socio-demographic and health information was collected in combination with dried blood spots for about 6500 individuals of all ages, which were analysed to detect IgG and IgM antibodies against four specific proteins of SARS-CoV-2 in a bead-based multiplex immunoassay. We evaluated spatio-temporal patterns in COVID-19 infection history and its associations with several geographic, socio-economic and demographic factors via logistic regressions. RESULTS: Eighteen percent of people had been infected by April-June 2021, with seroprevalence increasing with individuals' age. COVID-19 primarily spread along the only paved road and in major towns during the first epidemic wave, subsequently spreading along secondary roads during the second wave to more remote areas. Wealthier individuals and those with occupations such as commerce and formal employment were at higher risk of being infected in the first wave. Adult mortality increased in 2020, particularly for older men for whom it nearly doubled up to nearly 40 deaths per 1000. Less than 10% of mortality in this period would be directly attributed to COVID-19 deaths if known infection fatality ratios are applied to observed seroprevalence in the district. CONCLUSION: Our study provides a very granular understanding on COVID-19 transmission and mortality in a rural population of sub-Saharan Africa and suggests that the disease burden in these areas may have been substantially underestimated.

Excess mortality associated with the COVID-19 pandemic during the 2020 and 2021 waves in Antananarivo, Madagascar.

INTRODUCTION: COVID-19-associated mortality remains difficult to estimate in sub-Saharan Africa because of the lack of comprehensive systems of death registration. Based on death registers referring to the capital city of Madagascar, we sought to estimate the excess mortality during the COVID-19 pandemic and calculate the loss of life expectancy. METHODS: Death records between 2016 and 2021 were used to estimate weekly excess mortality during the pandemic period. To infer its synchrony with circulation of SARS-CoV-2, a cross-wavelet analysis was performed. Life expectancy loss due to the COVID-19 pandemic was calculated by projecting mortality rates using the Lee and Carter model and extrapolating the prepandemic trends (1990-2019). Differences in life expectancy at birth were disaggregated by cause of death. RESULTS: Peaks of excess mortality in 2020-21 were associated with waves of COVID-19. Estimates of all-cause excess mortality were 38.5 and 64.9 per 100 000 inhabitants in 2020 and 2021, respectively, with excess mortality reaching ≥50% over 6 weeks. In 2021, we quantified a drop of 0.8 and 1.0 years in the life expectancy for men and women, respectively attributable to increased risks of death beyond the age of 60 years. CONCLUSION: We observed high excess mortality during the pandemic period, in particular around the peaks of SARS-CoV-2 circulation in Antananarivo. Our study highlights the need to implement death registration systems in low-income countries to document true toll of a pandemic.

Sociodemographic Variables Can Guide Prioritized Testing Strategies for Epidemic Control in Resource-Limited Contexts.

BACKGROUND: Targeted surveillance allows public health authorities to implement testing and isolation strategies when diagnostic resources are limited, and can be implemented via the consideration of social network topologies. However, it remains unclear how to implement such surveillance and control when network data are unavailable. METHODS: We evaluated the ability of sociodemographic proxies of degree centrality to guide prioritized testing of infected individuals compared to known degree centrality. Proxies were estimated via readily available sociodemographic variables (age, gender, marital status, educational attainment, household size). We simulated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemics via a susceptible-exposed-infected-recovered individual-based model on 2 contact networks from rural Madagascar to test applicability of these findings to low-resource contexts. RESULTS: Targeted testing using sociodemographic proxies performed similarly to targeted testing using known degree centralities. At low testing capacity, using proxies reduced infection burden by 22%-33% while using 20% fewer tests, compared to random testing. By comparison, using known degree centrality reduced the infection burden by 31%-44% while using 26%-29% fewer tests. CONCLUSIONS: We demonstrate that incorporating social network information into epidemic control strategies is an effective countermeasure to low testing capacity and can be implemented via sociodemographic proxies when social network data are unavailable.

Climatic, land-use and socio-economic factors can predict malaria dynamics at fine spatial scales relevant to local health actors: Evidence from rural Madagascar.

While much progress has been achieved over the last decades, malaria surveillance and control remain a challenge in countries with limited health care access and resources. High-resolution predictions of malaria incidence using routine surveillance data could represent a powerful tool to health practitioners by targeting malaria control activities where and when they are most needed. Here, we investigate the predictors of spatio-temporal malaria dynamics in rural Madagascar, estimated from facility-based passive surveillance data. Specifically, this study integrates climate, land-use, and representative household survey data to explain and predict malaria dynamics at a high spatial resolution (i.e., by Fokontany, a cluster of villages) relevant to health care practitioners. Combining generalized linear mixed models (GLMM) and path analyses, we found that socio-economic, land use and climatic variables are all important predictors of monthly malaria incidence at fine spatial scales, via both direct and indirect effects. In addition, out-of-sample predictions from our model were able to identify 58% of the Fokontany in the top quintile for malaria incidence and account for 77% of the variation in the Fokontany incidence rank. These results suggest that it is possible to build a predictive framework using environmental and social predictors that can be complementary to standard surveillance systems and help inform control strategies by field actors at local scales.

Ecological and socioeconomic factors associated with the human burden of environmentally mediated pathogens: a global analysis.

BACKGROUND: Billions of people living in poverty are at risk of environmentally mediated infectious diseases-that is, pathogens with environmental reservoirs that affect disease persistence and control and where environmental control of pathogens can reduce human risk. The complex ecology of these diseases creates a global health problem not easily solved with medical treatment alone. METHODS: We quantified the current global disease burden caused by environmentally mediated infectious diseases and used a structural equation model to explore environmental and socioeconomic factors associated with the human burden of environmentally mediated pathogens across all countries. FINDINGS: We found that around 80% (455 of 560) of WHO-tracked pathogen species known to infect humans are environmentally mediated, causing about 40% (129 488 of 359 341 disability-adjusted life years) of contemporary infectious disease burden (global loss of 130 million years of healthy life annually). The majority of this environmentally mediated disease burden occurs in tropical countries, and the poorest countries carry the highest burdens across all latitudes. We found weak associations between disease burden and biodiversity or agricultural land use at the global scale. In contrast, the proportion of people with rural poor livelihoods in a country was a strong proximate indicator of environmentally mediated infectious disease burden. Political stability and wealth were associated with improved sanitation, better health care, and lower proportions of rural poverty, indirectly resulting in lower burdens of environmentally mediated infections. Rarely, environmentally mediated pathogens can evolve into global pandemics (eg, HIV, COVID-19) affecting even the wealthiest communities. INTERPRETATION: The high and uneven burden of environmentally mediated infections highlights the need for innovative social and ecological interventions to complement biomedical advances in the pursuit of global health and sustainability goals. FUNDING: Bill & Melinda Gates Foundation, National Institutes of Health, National Science Foundation, Alfred P. Sloan Foundation, National Institute for Mathematical and Biological Synthesis, Stanford University, and the US Defense Advanced Research Projects Agency.

Proactive community case management decreased malaria prevalence in rural Madagascar: results from a cluster randomized trial.

BACKGROUND: Malaria remains a leading cause of morbidity and mortality worldwide, with progress in malaria control stalling in recent years. Proactive community case management (pro-CCM) has been shown to increase access to diagnosis and treatment and reduce malaria burden. However, lack of experimental evidence may hinder the wider adoption of this intervention. We conducted a cluster randomized community intervention trial to assess the efficacy of pro-CCM at decreasing malaria prevalence in rural endemic areas of Madagascar. METHODS: Twenty-two fokontany (smallest administrative unit) of the Mananjary district in southeast Madagascar were selected and randomized 1:1 to pro-CCM (intervention) or conventional integrated community case management (iCCM). Residents of all ages in the intervention arm were visited by a community health worker every 2 weeks from March to October 2017 and screened for fever; those with fever were tested by a rapid diagnostic test (RDT) and treated if positive. Malaria prevalence was assessed using RDTs on all consenting study area residents prior to and following the intervention. Hemoglobin was measured among women of reproductive age. Intervention impact was assessed via difference-in-differences analyses using logistic regressions in generalized estimating equations. RESULTS: A total of 27,087 and 20,475 individuals participated at baseline and endline, respectively. Malaria prevalence decreased from 8.0 to 5.4% in the intervention arm for individuals of all ages and from 6.8 to 5.7% in the control arm. Pro-CCM was associated with a significant reduction in the odds of malaria positivity in children less than 15 years (OR = 0.59; 95% CI [0.38-0.91]), but not in older age groups. There was no impact on anemia among women of reproductive age. CONCLUSION: This trial suggests that pro-CCM approaches could help reduce malaria burden in rural endemic areas of low- and middle-income countries, but their impact may be limited to younger age groups with the highest malaria burden. TRIAL REGISTRATION: NCT05223933. Registered on February 4, 2022.

Identification of factors associated with residual malaria transmission using school-based serological surveys in settings pursuing elimination.

BACKGROUND: Targeted research on residual malaria transmission is important to improve strategies in settings pursuing elimination, where transmission reductions prove challenging. This study aimed to detect and characterize spatial heterogeneity and factors associated with Plasmodium falciparum infections and exposure, P. falciparum apical membrane antigen 1 (PfAMA1) antibody (Ab) response, in the Central Highlands of Madagascar (CHL). METHODS: From May to July 2014, a cross-sectional school-based survey was carried out in 182 fokontany (villages) within 7 health districts of the CHL. Rapid diagnostic tests (RDTs) and a bead-based immunoassay including PfAMA1 antigen biomarker were used to estimate malaria prevalence and seroprevalence, respectively. Local Moran's I index was used to detect spatial "hotspots". Remotely sensed environmental data-temperature, vegetation indices, land covers, and elevation-were used in multivariable mixed-effects logistic regression models to characterize factors associated with malaria infection and cumulative exposure. RESULTS: Among 6,293 school-children ages 2-14 years surveyed, RDT prevalence was low at 0.8% (95% CI 0.6-1.1%), while PfAMA1 Ab seroprevalence was 7.0% (95% CI 6.4-7.7%). Hotspots of PfAMA1 Ab seroprevalence were observed in two districts (Ankazobe and Mandoto). Seroprevalence increased for children living > 5 km from a health centre (adjusted odds ratio (OR) = 1.6, 95% CI 1.2-2.2), and for those experiencing a fever episode in the previous 2 weeks (OR 1.7, 95% CI 1.2-2.4), but decreased at higher elevation (for each 100-m increase, OR = 0.7, 95% CI 0.6-0.8). A clear age pattern was observed whereby children 9-10 years old had an OR of 1.8 (95% CI 1.2-2.4), children 11-12 years an OR of 3.7 (95% CI 2.8-5.0), and children 13-14 years an OR of 5.7 (95% CI 4.0-8.0) for seropositivity, compared with younger children (2-8 years). CONCLUSION: The use of serology in this study provided a better understanding of malaria hotspots and associated factors, revealing a pattern of higher transmission linked to geographical barriers in health care access. The integration of antibody-assays into existing surveillance activities could improve exposure assessment, and may help to monitor the effectiveness of malaria control efforts and adapt elimination interventions.

Evidence gaps and diversity among potential win-win solutions for conservation and human infectious disease control.

As sustainable development practitioners have worked to "ensure healthy lives and promote well-being for all" and "conserve life on land and below water", what progress has been made with win-win interventions that reduce human infectious disease burdens while advancing conservation goals? Using a systematic literature review, we identified 46 proposed solutions, which we then investigated individually using targeted literature reviews. The proposed solutions addressed diverse conservation threats and human infectious diseases, and thus, the proposed interventions varied in scale, costs, and impacts. Some potential solutions had medium-quality to high-quality evidence for previous success in achieving proposed impacts in one or both sectors. However, there were notable evidence gaps within and among solutions, highlighting opportunities for further research and adaptive implementation. Stakeholders seeking win-win interventions can explore this Review and an online database to find and tailor a relevant solution or brainstorm new solutions.

Impact of health system strengthening on delivery strategies to improve child immunisation coverage and inequalities in rural Madagascar.

BACKGROUND: To reach global immunisation goals, national programmes need to balance routine immunisation at health facilities with vaccination campaigns and other outreach activities (eg, vaccination weeks), which boost coverage at particular times and help reduce geographical inequalities. However, where routine immunisation is weak, an over-reliance on vaccination campaigns may lead to heterogeneous coverage. Here, we assessed the impact of a health system strengthening (HSS) intervention on the relative contribution of routine immunisation and outreach activities to reach immunisation goals in rural Madagascar. METHODS: We obtained data from health centres in Ifanadiana district on the monthly number of recommended vaccines (BCG, measles, diphtheria, tetanus and pertussis (DTP) and polio) delivered to children, during 2014-2018. We also analysed data from a district-representative cohort carried out every 2 years in over 1500 households in 2014-2018. We compared changes inside and outside the HSS catchment in the delivery of recommended vaccines, population-level vaccination coverage, geographical and economic inequalities in coverage, and timeliness of vaccination. The impact of HSS was quantified via mixed-effects logistic regressions. RESULTS: The HSS intervention was associated with a significant increase in immunisation rates (OR between 1.22 for measles and 1.49 for DTP), which diminished over time. Outreach activities were associated with a doubling in immunisation rates, but their effect was smaller in the HSS catchment. Analysis of cohort data revealed that HSS was associated with higher vaccination coverage (OR between 1.18 per year of HSS for measles and 1.43 for BCG), a reduction in economic inequality, and a higher proportion of timely vaccinations. Yet, the lower contribution of outreach activities in the HSS catchment was associated with persistent inequalities in geographical coverage, which prevented achieving international coverage targets. CONCLUSION: Investment in stronger primary care systems can improve vaccination coverage, reduce inequalities and improve the timeliness of vaccination via increases in routine immunisations.

Geographic barriers to care persist at the community healthcare level: Evidence from rural Madagascar.

Geographic distance is a critical barrier to healthcare access, particularly for rural communities with poor transportation infrastructure who rely on non-motorized transportation. There is broad consensus on the importance of community health workers (CHWs) to reduce the effects of geographic isolation on healthcare access. Due to a lack of fine-scale spatial data and individual patient records, little is known about the precise effects of CHWs on removing geographic barriers at this level of the healthcare system. Relying on a high-quality, crowd-sourced dataset that includes all paths and buildings in the area, we explored the impact of geographic distance from CHWs on the use of CHW services for children under 5 years in the rural district of Ifanadiana, southeastern Madagascar from 2018-2021. We then used this analysis to determine key features of an optimal geographic design of the CHW system, specifically optimizing a single CHW location or installing additional CHW sites. We found that consultation rates by CHWs decreased with increasing distance patients travel to the CHW by approximately 28.1% per km. The optimization exercise revealed that the majority of CHW sites (50/80) were already in an optimal location or shared an optimal location with a primary health clinic. Relocating the remaining CHW sites based on a geographic optimum was predicted to increase consultation rates by only 7.4%. On the other hand, adding a second CHW site was predicted to increase consultation rates by 31.5%, with a larger effect in more geographically dispersed catchments. Geographic distance remains a barrier at the level of the CHW, but optimizing CHW site location based on geography alone will not result in large gains in consultation rates. Rather, alternative strategies, such as the creation of additional CHW sites or the implementation of proactive care, should be considered.

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.

Baseline malaria prevalence and care-seeking behaviours in rural Madagascar prior to a trial to expand malaria community case management to all ages.

BACKGROUND: Integrated community case management of malaria, pneumonia, and diarrhoea can reduce mortality in children under five years (CU5) in resource-poor countries. There is growing interest in expanding malaria community case management (mCCM) to older individuals, but limited empirical evidence exists to guide this expansion. As part of a two-year cluster-randomized trial of mCCM expansion to all ages in southeastern Madagascar, a cross-sectional survey was conducted to assess baseline malaria prevalence and healthcare-seeking behaviours. METHODS: Two enumeration areas (EAs) were randomly chosen from each catchment area of the 30 health facilities (HFs) in Farafangana district designated for the mCCM age expansion trial; 28 households were randomly selected from each EA for the survey. All household members were asked about recent illness and care-seeking, and malaria prevalence was assessed by rapid diagnostic test (RDT) among children < 15 years of age. Weighted population estimates and Rao-Scott chi-squared tests were used to examine illness, care-seeking, malaria case management, and malaria prevalence patterns. RESULTS: Illness in the two weeks prior to the survey was reported by 459 (6.7%) of 8050 respondents in 334 of 1458 households surveyed. Most individuals noting illness (375/459; 82.3%) reported fever. Of those reporting fever, 28.7% (112/375) sought care; this did not vary by participant age (p = 0.66). Most participants seeking care for fever visited public HFs (48/112, 46.8%), or community healthcare volunteers (CHVs) (40/112, 31.0%). Of those presenting with fever at HFs or to CHVs, 87.0% and 71.0%, respectively, reported being tested for malaria. RDT positivity among 3,316 tested children < 15 years was 25.4% (CI: 21.5-29.4%) and increased with age: 16.9% in CU5 versus 31.8% in 5-14-year-olds (p < 0.0001). Among RDT-positive individuals, 28.4% of CU5 and 18.5% of 5-14-year-olds reported fever in the two weeks prior to survey (p = 0.044). CONCLUSIONS: The higher prevalence of malaria among older individuals coupled with high rates of malaria testing for those who sought care at CHVs suggest that expanding mCCM to older individuals may substantially increase the number of infected individuals with improved access to care, which could have additional favorable effects on malaria transmission.

Integrating Health Systems and Science to Respond to COVID-19 in a Model District of Rural Madagascar.

There are many outstanding questions about how to control the global COVID-19 pandemic. The information void has been especially stark in the World Health Organization Africa Region, which has low per capita reported cases, low testing rates, low access to therapeutic drugs, and has the longest wait for vaccines. As with all disease, the central challenge in responding to COVID-19 is that it requires integrating complex health systems that incorporate prevention, testing, front line health care, and reliable data to inform policies and their implementation within a relevant timeframe. It requires that the population can rely on the health system, and decision-makers can rely on the data. To understand the process and challenges of such an integrated response in an under-resourced rural African setting, we present the COVID-19 strategy in Ifanadiana District, where a partnership between Malagasy Ministry of Public Health (MoPH) and non-governmental organizations integrates prevention, diagnosis, surveillance, and treatment, in the context of a model health system. These efforts touch every level of the health system in the district-community, primary care centers, hospital-including the establishment of the only RT-PCR lab for SARS-CoV-2 testing outside of the capital. Starting in March of 2021, a second wave of COVID-19 occurred in Madagascar, but there remain fewer cases in Ifanadiana than for many other diseases (e.g., malaria). At the Ifanadiana District Hospital, there have been two deaths that are officially attributed to COVID-19. Here, we describe the main components and challenges of this integrated response, the broad epidemiological contours of the epidemic, and how complex data sources can be developed to address many questions of COVID-19 science. Because of data limitations, it still remains unclear how this epidemic will affect rural areas of Madagascar and other developing countries where health system utilization is relatively low and there is limited capacity to diagnose and treat COVID-19 patients. Widespread population based seroprevalence studies are being implemented in Ifanadiana to inform the COVID-19 response strategy as health systems must simultaneously manage perennial and endemic disease threats.

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.

Socio-demographic, not environmental, risk factors explain fine-scale spatial patterns of diarrhoeal disease in Ifanadiana, rural Madagascar.

Precision health mapping is a technique that uses spatial relationships between socio-ecological variables and disease to map the spatial distribution of disease, particularly for diseases with strong environmental signatures, such as diarrhoeal disease (DD). While some studies use GPS-tagged location data, other precision health mapping efforts rely heavily on data collected at coarse-spatial scales and may not produce operationally relevant predictions at fine enough spatio-temporal scales to inform local health programmes. We use two fine-scale health datasets collected in a rural district of Madagascar to identify socio-ecological covariates associated with childhood DD. We constructed generalized linear mixed models including socio-demographic, climatic and landcover variables and estimated variable importance via multi-model inference. We find that socio-demographic variables, and not environmental variables, are strong predictors of the spatial distribution of disease risk at both individual and commune-level (cluster of villages) spatial scales. Climatic variables predicted strong seasonality in DD, with the highest incidence in colder, drier months, but did not explain spatial patterns. Interestingly, the occurrence of a national holiday was highly predictive of increased DD incidence, highlighting the need for including cultural factors in modelling efforts. Our findings suggest that precision health mapping efforts that do not include socio-demographic covariates may have reduced explanatory power at the local scale. More research is needed to better define the set of conditions under which the application of precision health mapping can be operationally useful to local public health professionals.

Estimating the local spatio-temporal distribution of malaria from routine health information systems in areas of low health care access and reporting.

BACKGROUND: Reliable surveillance systems are essential for identifying disease outbreaks and allocating resources to ensure universal access to diagnostics and treatment for endemic diseases. Yet, most countries with high disease burdens rely entirely on facility-based passive surveillance systems, which miss the vast majority of cases in rural settings with low access to health care. This is especially true for malaria, for which the World Health Organization estimates that routine surveillance detects only 14% of global cases. The goal of this study was to develop a novel method to obtain accurate estimates of disease spatio-temporal incidence at very local scales from routine passive surveillance, less biased by populations' financial and geographic access to care. METHODS: We use a geographically explicit dataset with residences of the 73,022 malaria cases confirmed at health centers in the Ifanadiana District in Madagascar from 2014 to 2017. Malaria incidence was adjusted to account for underreporting due to stock-outs of rapid diagnostic tests and variable access to healthcare. A benchmark multiplier was combined with a health care utilization index obtained from statistical models of non-malaria patients. Variations to the multiplier and several strategies for pooling neighboring communities together were explored to allow for fine-tuning of the final estimates. Separate analyses were carried out for individuals of all ages and for children under five. Cross-validation criteria were developed based on overall incidence, trends in financial and geographical access to health care, and consistency with geographic distribution in a district-representative cohort. The most plausible sets of estimates were then identified based on these criteria. RESULTS: Passive surveillance was estimated to have missed about 4 in every 5 malaria cases among all individuals and 2 out of every 3 cases among children under five. Adjusted malaria estimates were less biased by differences in populations' financial and geographic access to care. Average adjusted monthly malaria incidence was nearly four times higher during the high transmission season than during the low transmission season. By gathering patient-level data and removing systematic biases in the dataset, the spatial resolution of passive malaria surveillance was improved over ten-fold. Geographic distribution in the adjusted dataset revealed high transmission clusters in low elevation areas in the northeast and southeast of the district that were stable across seasons and transmission years. CONCLUSIONS: Understanding local disease dynamics from routine passive surveillance data can be a key step towards achieving universal access to diagnostics and treatment. Methods presented here could be scaled-up thanks to the increasing availability of e-health disease surveillance platforms for malaria and other diseases across the developing world.