About

Matthew Bonds is an associate professor of global health and social medicine at Harvard Medical School. He holds PhDs in economics and disease ecology from the University of Georgia. His research focuses on the ecology of poverty and economic development, as well as the science of implementing global health delivery systems. Bonds is also the co-founder and scientific director of PIVOT, an organization working with the Madagascar government to establish a district-level model health system serving over 200,000 people. His work involves developing novel data systems across all levels of care—community, primary, and secondary—to pioneer a new science of health system transformation, with some of the most rigorously evaluated population-level impacts in the world.

Research topics

• Medicine
• Economics
• Political Science
• Business
• Microeconomics
• Psychology
• Economic growth
• Risk analysis (engineering)
• Public relations
• Environmental health
• Social psychology

Selected publications

• Leveraging spatial structure to design spatially-targeted malaria interventions at the community-scale

  medRxiv · 2026-02-15

  articleOpen access

  ABSTRACT Progress in malaria control has stagnated since the early 21st century in many countries, requiring new approaches such as the use of spatially-targeted interventions. Evidence on the effectiveness of spatially-targeted interventions is mixed. Their success can be dependent on whether the setting is endemic, the metrics used to target the intervention, and the spatial resolution and scale of deployment. We developed a two-age-class, spatially-explicit model of malaria at the community-scale for a district in southeastern Madagascar, accounting for environmental heterogeneity and human mobility. The model was fit to field-based case notifications and malaria prevalence data and then used to simulate three interventions: indoor residual spraying (IRS), long-lasting insecticide-treated nets (LLIN), and active case detection (ACD). We compared five spatial targeting scenarios for each simulated intervention: (i) equally distributed, (ii) targeting communities nearest or (iii) furthest from clinics, (iv) targeting communities with highest incidence, and (v) targeting communities that are spatially central. The non-targeted intervention was generally the most effective, but the least resource efficient. The second most effective intervention was based on spatial centrality, which reached a larger population while using fewer transportation resources than the equally distributed. No combination of interventions was able to eliminate malaria in the district, although a “perfect” ACD intervention could avert 100% of severe malaria cases. These results highlight the potential for targeted malaria interventions, especially in low-income settings, that take into account spatial structure in the human population and mobility to reduce malaria burden using fewer resources than conventional district-wide interventions.

  PublisherOA PDFDOI

• What Does It Take to Map a Country? Scaling OpenStreetMap Mapping for Accurate Health Accessibility Modelling in Madagascar

  medRxiv · 2026-03-27

  articleOpen access

  Abstract Comprehensive geographic data are essential to accurately model geographic accessibility to healthcare and to guide equitable health system planning and implementation. In low-income countries, however, incomplete road and building data in global databases such as OpenStreetMap (OSM) limit the precision and operational applications of geographic accessibility models. Following a successful pilot in one district of Madagascar, we evaluated the scalability of an exhaustive mapping approach to produce highly granulated household-level accessibility estimates at regional and national levels. Using satellite imagery and the OSM platform, we mapped all buildings, roads, footpaths, and rice fields across seven additional districts in southeastern Madagascar. We estimated travel routes, distance and travel time between each household and the nearest primary health center (PHC) or community health site (CHS) using the OSM Routing Machine, combined with predictions of travel speed from a locally calibrated statistical model. We then assessed population density and mapping completeness for roads and buildings in our study area and across Madagascar using AI-generated reference datasets (Microsoft and Facebook/MapWithAI) and estimated corresponding mapping times. Finally, we estimated the resources required in person-years to scale this approach across Madagascar using two different extrapolation methods. Nearly one and a half million buildings and 197,000 km of footpaths were added to OSM across the eight mapped districts, for a total area of about 30,200 km 2 . Between 24 % and 65 % of the population lived within one hour of a PHC depending on the district, and 87 %–99 % lived within one hour of a CHS. Most Malagasy districts were classified as having low completeness for both buildings and roads. Scaling up the approach to cover the entire country would require between 220 and 350 person-years depending on the extrapolation method and assumptions used. Mapping an entire country with sufficient detail to precisely model healthcare accessibility for every household is feasible but resource-intensive. Combining human mapping, participatory approaches, and AI-assisted datasets can substantially improve OSM completeness and generate actionable, high-resolution travel-time data for health planning. Our findings provide a roadmap for Madagascar and other countries seeking to develop national-scale geospatial infrastructure for sustainable development and universal health coverage.

  PublisherOA PDFDOI

• Assessing the impact of scaling up a health systems strengthening initiative in southeastern Madagascar: baseline socio-economic and health conditions in Vatovavy Region, Madagascar

  Research Square · 2026-01-28

  preprintOpen access
  PublisherOA PDFDOI

• Changes in child mortality and population health following 10 years of health systems strengthening in rural Madagascar: A longitudinal cohort study

  PLoS Medicine · 2025-10-07

  articleOpen accessCorresponding

  BACKGROUND: Reducing child mortality rates is a unifying goal of the global health and international development communities. In Africa, unambiguous empirical evidence on how health system interventions can drive such reductions has been elusive. This gap in the literature is due to challenges in implementing system-level changes on a scale and pace to have measurable impacts on mortality, and the challenges of collecting adequate data on the population and programs over sufficient time with plausible counterfactuals. This study aimed to assess the population health impact of the first decade of implementation of a health system strengthening (HSS) intervention in a rural district of Madagascar. METHODS AND FINDINGS: The study is a prospective quasi-experiment using a district-representative cohort of over 1,500 households (five waves of survey collection), in combination with patient data collected across different levels of care (community health workers and health facilities), geographic information systems, and programmatic data to assess changes in mortality, healthcare coverage and utilization from 2014 to 2023. The HSS intervention integrates support to clinical programs with strengthened health system building blocks and social protection at all levels of care of a district health system (community health, primary care centers, and hospital). Under-five, infant and neonatal mortality were estimated at the population level using the synthetic life-table method for DHS surveys. Impact of the HSS intervention on healthcare coverage and utilization was assessed through interrupted time-series analyses. Changes in geographic and financial inequalities in coverage indicators were studied via the relative concentration index and slope index of inequality. Our results show that trends in child mortality rates (neonatal, infant, under-five) decreased in the initial HSS intervention area from 2014 to 2023, but increased in the comparison area as well as the rest of the country over the same period. The HSS intervention was associated with statistically significant increases in service coverage and primary care utilization for a wide range of maternal and child health indicators, as well as reductions in geographic and financial barriers to care. The main limitations of this study were that the intervention was not randomized, and that changes in child mortality were estimated from 5-year averages from repeated cross sections, with overlapping time windows that prevented formal integration into the statistical modeling framework used for coverage indicators. CONCLUSIONS: By measuring both indirect and direct impacts of HSS on population health in a context where health and economic indicators are not otherwise improving, these results provide converging evidence on how strengthening health systems, from community health to hospitals, in low-resource settings increases overall utilization of services, reduces inequities in access to those services, and corresponds with reductions in mortality.

  PublisherDOI

• Designing and evaluating a health system resilient to extreme weather events in rural Madagascar

  medRxiv · 2025-01-14

  preprintOpen accessSenior author

  ABSTRACT Adapting health systems for climate change can lessen the negative impact of climate change on human health. Even when not targeting climate-health links explicitly, broad health system strengthening interventions (HSSi’s) can ensure that the health workforce, infrastructure, and networks are robust enough to respond to and recover from climate-driven shocks. We explored the ability of an HSSi in a rural health district of southeastern Madagascar to serve as a climate change adaptation in response to cyclone Batsirai in 2022. The HSSi provides support for programs and health system infrastructure while introducing enhanced protocols and prioritizing rapid, local learning and adaptation. We conducted interrupted time series analyses of eight indicators of infectious disease and health system performance to assess the impact of Batsirai on two zones of the HSSi. We then examined how traditional domains of HSS, such as physical and human resources, combined with less formal domains, such as collective values, influenced health system resilience during this time. We found that the majority of indicators were resilient to cyclone Batsirai, with only vaccination rates affected in the two months following the cyclone, particularly in the zone where the HSSi had only begun 8 months prior. Changes in long-term trends were rare, and, when observed, revealed a slight slowing of progress, but not a regression to historical levels. After re-establishing the road network and providing additional supplies through an emergency response, the health system was able to resume routine service delivery without further external input and health system indicators continued to improve. The agility and responsiveness of the health workforce was enabled by formalized protocols, a culture of flexibility, open communication and data-informed action. HSSi’s that are designed to encourage local adaptation may increase health systems’ resilience to extreme weather events, resulting in health systems better adapted to climate change overall. TEASER KEY MESSAGE By improving overall service availability and readiness and establishing collective values that prioritize local and rapid adaptation, broad health system strengthening initiatives can create climate-resilient health systems. KEY MESSAGES Following cyclone Batsirai, a strengthened district health system in Madagascar mitigated the impact of this climate-driven shock on health system functioning. This was due to collective values of patient care, innovation, and data-informed action, in addition to supporting health resources and infrastructure. Rapid restoration of the transportation network via food-for-work programs and other external sources of support helped primary care facilities reopen quickly and resume admitting patients. Such coordinated approaches across sectors are needed to support health system responses to climate-driven natural disasters, and restore routine functioning.

  PublisherOA PDFDOI

• Designing and Evaluating a Health System Resilient to Extreme Weather Events in Rural Madagascar

  Annals of Global Health · 2025-07-22

  articleOpen accessSenior author

  Background: Adapting health systems for climate change can lessen the negative impact of climate change on human health. Even when not targeting climate-health links explicitly, broad health system strengthening interventions (HSSis) can ensure that the health workforce, infrastructure, and networks are robust enough to respond to and recover from climate-driven shocks. Objective: We explored the ability of an HSSi in a rural health district of southeastern Madagascar to serve as a climate change adaptation in response to Cyclone Batsirai in 2022. Method: We conducted interrupted time series analyses of eight indicators of infectious disease and health system performance to assess the impact of Batsirai on two zones of the HSSi. We then examined how traditional domains of HSS, such as physical and human resources, combined with less formal domains, such as collective values, influenced health system resilience during this time. Findings: We found that the majority of indicators were resilient to Cyclone Batsirai, with only vaccination rates affected in the two months following the cyclone, particularly in the zone where the HSSi had only begun eight months prior. Changes in long-term trends were rare, and, when observed, revealed a slight slowing of progress, but not a regression to historical levels. After re-establishing the road network and providing additional supplies through an emergency response, the health system was able to resume routine service delivery without further external input, and health system indicators continued to improve. The agility and responsiveness of the health workforce were enabled by formalized protocols, a culture of flexibility, open communication, and data-informed action. Conclusions: HSSis that are designed to encourage local adaptation may increase health systems’ resilience to extreme weather events, resulting in health systems better adapted to climate change overall.

  PublisherOA PDFDOI

•  Increasing the resolution of malaria early warning systems for use by local health actors

  Malaria Journal · 2025-01-29 · 7 citations

  articleOpen access

  BACKGROUND: The increasing availability of electronic health system data and remotely-sensed environmental variables has led to the emergence of statistical models capable of producing malaria forecasts. Many of these models have been operationalized into malaria early warning systems (MEWSs), which provide predictions of malaria dynamics several months in advance at national and regional levels. However, MEWSs rarely produce predictions at the village-level, the operational scale of community health systems and the first point of contact for the majority of rural populations in malaria-endemic countries. METHODS: This study developed a hyper-local MEWS for use within a health-system strengthening intervention in rural Madagascar. It combined bias-corrected, village-level case notification data with remotely sensed environmental variables at spatial scales as fine as a 10 m resolution. A spatio-temporal hierarchical generalized linear regression model was trained on monthly malaria case data from 195 communities from 2017 to 2020 and evaluated via cross-validation. The model was then integrated into an automated workflow with environmental data updated monthly to create a continuously updating MEWS capable of predicting malaria cases up to three months in advance at the village-level. Predictions were transformed into indicators relevant to health system actors by estimating the quantities of medical supplies required at each health clinic and the number of cases remaining untreated at the community level. RESULTS: The statistical model was able to accurately reproduce village-level case data, performing nearly five times as well as a null model during cross-validation. The dynamic environmental variables, particularly those associated with standing water and rice field dynamics, were strongly associated with malaria incidence, allowing the model to accurately predict future incidence rates. The MEWS represented an improvement of over 50% compared to existing stock order quantification methods when applied retrospectively. CONCLUSION: This study demonstrates the feasibility of developing an automatic, hyper-local MEWS leveraging remotely-sensed environmental data at fine spatial scales. As health system data become increasingly digitized, this method can be easily applied to other regions and be updated with near real-time health data to further increase performance.

  PublisherOA PDFDOI

• Persistence of geographic barriers to maternal care services following a health system strengthening initiative in rural Madagascar

  BMC Pregnancy and Childbirth · 2025-10-01 · 1 citations

  articleOpen access

  BACKGROUND: Geographic access to healthcare continues to pose a significant challenge for pregnant women in rural areas of sub-Saharan Africa, resulting in consistently high rates of maternal mortality. Geographic barriers can persist even in settings where financial barriers have been reduced and health system strengthening (HSS) efforts are in place. The aim of this study is to gain a precise understanding of spatiotemporal changes in access to and utilization of maternal care services in a rural district of Madagascar benefiting from HSS support. METHODS: We collected geolocated monthly information at the village level on antenatal care visits, deliveries and postnatal visits from the registries of 18 public primary health centers in Ifanadiana District, from 2016 to 2018. Similar data were collected from a district-representative cohort via surveys on over 1500 households done in 2016 and 2018. We estimated precise travel time from each village to the nearest health center to understand spatio-temporal variations in maternal care access, and to assess the impact of geographic barriers via statistical analyses while controlling for health system factors. RESULTS: Women who lived within a one-hour walk from a health facility in the HSS catchment area had rates of per capita utilization of most maternal health services were roughly twice that those who lived 1-2 h away and three times higher than those who lived over 2 h away (e.g. relative change for delivery at a health center was 0.60 [0.53-0.67] and 0.40 [0.36-0.45] for women living 1-2 h and over 2 h from a facility, respectively). The exception was the first antenatal care visit (ANC1), for which travel time had more modest effect (e.g. relative change of 0.72 [0.67-0.77] over 2 h). Improvements to primary care services due to HSS in this setting were only observed among women living within two hours from health centers. Statistical models revealed that women's travel time from a health facility was the strongest determinant of maternal care service utilization. CONCLUSION: This study shows how a combination of geo-located health system information and population-representative data can help assess the impact of geographical barriers to maternal care in rural areas of sub-Saharan Africa. It highlights that women who live more than 2 h from a health facility had virtually no access to maternal health services despite efforts in place to reduce financial barriers to care and strengthen the health system.

  PublisherOA PDFDOI

• Referee report. For: Enhancing quantitative capacity for the health sector in post-Ebola Liberia, a tracer study of a locally developed and owned coding and biostatistics program [version 1; peer review: 2 approved]

  Faculty of 1000 Research Ltd · 2025-01-01

  peer-reviewOpen access1st authorCorresponding
  PublisherDOI

• Mapping and Modeling the Social and Ecological Determinants of Vector-Borne Disease Risk: A Case Study of Human African Trypanosomiasis

  2024-01-01

  book-chapter
  PublisherDOI

Recent grants

• The economic impacts of community-based integrated health care systems in rural R

  NIH · $666k · 2010–2015

Frequent coauthors

• Andrés Garchitorena

  595 shared

• Ann C. Miller

  Boston VA Research Institute

  193 shared

• Laura Cordier

  164 shared

• Felana Ihantamalala

  Harvard Global Health Institute

  155 shared

• Karen E. Finnegan

  Harvard University

  150 shared

• Benjamín Roche

  Maladies Infectieuses et Vecteurs: Écologie, Génétique, Évolution et Contrôle

  103 shared

• Calistus N. Ngonghala

  University of Florida

  95 shared

• Mauricianot Randriamihaja

  Université de Montpellier

  95 shared

Education

• Ph.D., African Studies

  Harvard University

  2009

• M.A., African Studies

  University of California, Berkeley

  2003

• B.A., African Studies

  University of California, Berkeley

  2001

Awards & honors

• K01 Award from the NIH Fogarty International Center
• Scholar Award in Complex Systems Science from the James S. M…
• Rainer Arnhold Fellowship from the Mulago Foundation