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The most recent global estimates of the number of pregnancies at risk of Plasmodium falciparum and Plasmodium vivax malaria infection are from 2007. To inform global malaria prevention and control efforts, we aimed to estimate the global distribution of pregnancies at risk of malaria infection from 2007 to 2020.We used estimates from the Malaria Atlas Project on the total population living in areas of P falciparum and P vivax transmission, combined with country-specific demographic data on women of reproductive age, fertility rates, induced abortions, and stillbirths, to derive the annual number of pregnancies overall, by parasite species, and by endemicity strata from 2007 to 2020. The definition of endemicity strata was based on the parasite point prevalence in individuals aged 2-10 years for P falciparum and 1-99 years for P vivax. We also did a sensitivity analysis in which we considered most of sub-Saharan Africa endemic for P vivax.In 2020, 121·9 million pregnancies occurred in malaria transmission areas, resulting in an estimated 70·9 million (58·1%) livebirths. The total number of pregnancies at risk of malaria was 52·9 million in the WHO South-East Asia (SEARO) region, 5·1 million in the Western Pacific (WPRO) region, 46·1 million in the Africa (AFRO) region, 11·1 million in the Eastern Mediterranean (EMRO) region, and 6·7 million in the Americas (AMRO) region. Between 2007 and 2020, pregnancies in areas of P falciparum transmission declined by 11·4% globally, despite an overall 7·0% increase in pregnancies, representing a decrease of 100·0% in the WHO Europe (EURO) region, 52·6% in WPRO, 51·5% in AMRO, 23·9% in EMRO, and 17·2% in SEARO, and a 25·4% increase in AFRO. Pregnancies in P vivax transmission areas fell by 42·8%, representing a decrease of 100·0% in EURO, 89·8% in WPRO, 48·4% in AMRO, 32·4% in EMRO, and 10·0% in SEARO, and a 25·8% increase in AFRO. Our sensitivity analysis suggests that the number of pregnancies at risk of P vivax infection could be seven-fold higher for AFRO if the whole of sub-Saharan Africa was considered endemic for P vivax.Between 2007 and 2020, substantial declines in the number of pregnancies at risk of malaria were seen globally. However, in AFRO, 25·4% more pregnancies were at risk of P falciparum or P vivax malaria than in 2007. This increase in the number at risk in AFRO comes despite the decline in malaria rates due to the rapidly rising population and the corresponding number of pregnancies in endemic areas. These estimates should guide priority setting for resource allocation to control malaria in pregnancy.BillMelinda Gates Foundation and Telethon Trust.

Summary Background Plasmodium vivax exacts a significant toll on health worldwide, yet few efforts to date have quantified the extent and temporal trends of its global distribution. Given the challenges associated with the proper diagnosis and treatment of P vivax , national malaria programmes—particularly those pursuing malaria elimination strategies—require up to date assessments of P vivax endemicity and disease impact. This study presents the first global maps of P vivax clinical burden from 2000 to 2017. Methods In this spatial and temporal modelling study, we adjusted routine malariometric surveillance data for known biases and used socioeconomic indicators to generate time series of the clinical burden of P vivax . These data informed Bayesian geospatial models, which produced fine-scale predictions of P vivax clinical incidence and infection prevalence over time. Within sub-Saharan Africa, where routine surveillance for P vivax is not standard practice, we combined predicted surfaces of Plasmodium falciparum with country-specific ratios of P vivax to P falciparum . These results were combined with surveillance-based outputs outside of Africa to generate global maps. Findings We present the first high-resolution maps of P vivax burden. These results are combined with those for P falciparum (published separately) to form the malaria estimates for the Global Burden of Disease 2017 study. The burden of P vivax malaria decreased by 41·6%, from 24·5 million cases (95% uncertainty interval 22·5–27·0) in 2000 to 14·3 million cases (13·7–15·0) in 2017. The Americas had a reduction of 56·8% (47·6–67·0) in total cases since 2000, while South-East Asia recorded declines of 50·5% (50·3–50·6) and the Western Pacific regions recorded declines of 51·3% (48·0–55·4). Europe achieved zero P vivax cases during the study period. Nonetheless, rates of decline have stalled in the past five years for many countries, with particular increases noted in regions affected by political and economic instability. Interpretation Our study highlights important spatial and temporal patterns in the clinical burden and prevalence of P vivax . Amid substantial progress worldwide, plateauing gains and areas of increased burden signal the potential for challenges that are greater than expected on the road to malaria elimination. These results support global monitoring systems and can inform the optimisation of diagnosis and treatment where P vivax has most impact. Funding Bill & Melinda Gates Foundation and the Wellcome Trust.

Insecticide-treated nets (ITNs) are one of the most widespread and impactful malaria interventions in Africa, yet a spatially-resolved time series of ITN coverage has never been published. Using data from multiple sources, we generate high-resolution maps of ITN access, use, and nets-per-capita annually from 2000 to 2020 across the 40 highest-burden African countries. Our findings support several existing hypotheses: that use is high among those with access, that nets are discarded more quickly than official policy presumes, and that effectively distributing nets grows more difficult as coverage increases. These results can inform both policy decisions and downstream malaria analyses.

Insecticide-treated nets (ITNs) are one of the most widespread and impactful malaria interventions in Africa, yet a spatially-resolved time series of ITN coverage has never been published. Using data from multiple sources, we generate high-resolution maps of ITN access, use, and nets-per-capita annually from 2000 to 2020 across the 40 highest-burden African countries. Our findings support several existing hypotheses: that use is high among those with access, that nets are discarded more quickly than official policy presumes, and that effectively distributing nets grows more difficult as coverage increases. The primary driving factors behind these findings are most likely strong cultural and social messaging around the importance of net use, low physical net durability, and a mixture of inherent commodity distribution challenges and less-than-optimal net allocation policies, respectively. These results can inform both policy decisions and downstream malaria analyses., Insecticide treated nets (ITNs) are an important part of malaria control in Africa and WHO targets aim for 80% coverage. This study estimates the spatio-temporal access and use of ITNs in Africa from 2000-2020, and shows that both metrics have improved over time but access remains below WHO targets.

Background Anti-malarial drugs play a critical role in reducing malaria morbidity and mortality, but their role is mediated by their effectiveness. Effectiveness is defined as the probability that an anti-malarial drug will successfully treat an individual infected with malaria parasites under routine health care delivery system. Anti-malarial drug effectiveness (AmE) is influenced by drug resistance, drug quality, health system quality, and patient adherence to drug use; its influence on malaria burden varies through space and time. Methods This study uses data from 232 efficacy trials comprised of 86,776 infected individuals to estimate the artemisinin-based and non-artemisinin-based AmE for treating falciparum malaria between 1991 and 2019. Bayesian spatiotemporal models were fitted and used to predict effectiveness at the pixel-level (5 km × 5 km). The median and interquartile ranges (IQR) of AmE are presented for all malaria-endemic countries. Results The global effectiveness of artemisinin-based drugs was 67.4% (IQR: 33.3–75.8), 70.1% (43.6–76.0) and 71.8% (46.9–76.4) for the 1991–2000, 2006–2010, and 2016–2019 periods, respectively. Countries in central Africa, a few in South America, and in the Asian region faced the challenge of lower effectiveness of artemisinin-based anti-malarials. However, improvements were seen after 2016, leaving only a few hotspots in Southeast Asia where resistance to artemisinin and partner drugs is currently problematic and in the central Africa where socio-demographic challenges limit effectiveness. The use of artemisinin-based combination therapy (ACT) with a competent partner drug and having multiple ACT as first-line treatment choice sustained high levels of effectiveness. High levels of access to healthcare, human resource capacity, education, and proximity to cities were associated with increased effectiveness. Effectiveness of non-artemisinin-based drugs was much lower than that of artemisinin-based with no improvement over time: 52.3% (17.9–74.9) for 1991–2000 and 55.5% (27.1–73.4) for 2011–2015. Overall, AmE for artemisinin-based and non-artemisinin-based drugs were, respectively, 29.6 and 36% below clinical efficacy as measured in anti-malarial drug trials. Conclusions This study provides evidence that health system performance, drug quality and patient adherence influence the effectiveness of anti-malarials used in treating uncomplicated falciparum malaria. These results provide guidance to countries’ treatment practises and are critical inputs for malaria prevalence and incidence models used to estimate national level malaria burden.

Background Substantial progress has been made in reducing the burden of malaria in Africa since 2000, but those gains could be jeopardised if the COVID-19 pandemic affects the availability of key malaria control interventions. The aim of this study was to evaluate plausible effects on malaria incidence and mortality under different levels of disruption to malaria control. Methods Using an established set of spatiotemporal Bayesian geostatistical models, we generated geospatial estimates across malaria-endemic African countries of the clinical case incidence and mortality of malaria, incorporating an updated database of parasite rate surveys, insecticide-treated net (ITN) coverage, and effective treatment rates. We established a baseline estimate for the anticipated malaria burden in Africa in the absence of COVID-19-related disruptions, and repeated the analysis for nine hypothetical scenarios in which effective treatment with an antimalarial drug and distribution of ITNs (both through routine channels and mass campaigns) were reduced to varying extents. Findings We estimated 215·2 (95% uncertainty interval 143·7–311·6) million cases and 386·4 (307·8–497·8) thousand deaths across malaria-endemic African countries in 2020 in our baseline scenario of undisrupted intervention coverage. With greater reductions in access to effective antimalarial drug treatment, our model predicted increasing numbers of cases and deaths: 224·1 (148·7–326·8) million cases and 487·9 (385·3–634·6) thousand deaths with a 25% reduction in antimalarial drug coverage; 233·1 (153·7–342·5) million cases and 597·4 (468·0–784·4) thousand deaths with a 50% reduction; and 242·3 (158·7–358·8) million cases and 715·2 (556·4–947·9) thousand deaths with a 75% reduction. Halting planned 2020 ITN mass distribution campaigns and reducing routine ITN distributions by 25%–75% also increased malaria burden to a total of 230·5 (151·6–343·3) million cases and 411·7 (322·8–545·5) thousand deaths with a 25% reduction; 232·8 (152·3–345·9) million cases and 415·5 (324·3–549·4) thousand deaths with a 50% reduction; and 234·0 (152·9–348·4) million cases and 417·6 (325·5–553·1) thousand deaths with a 75% reduction. When ITN coverage and antimalarial drug coverage were synchronously reduced, malaria burden increased to 240·5 (156·5–358·2) million cases and 520·9 (404·1–691·9) thousand deaths with a 25% reduction; 251·0 (162·2–377·0) million cases and 640·2 (492·0–856·7) thousand deaths with a 50% reduction; and 261·6 (167·7–396·8) million cases and 768·6 (586·1–1038·7) thousand deaths with a 75% reduction. Interpretation Under pessimistic scenarios, COVID-19-related disruption to malaria control in Africa could almost double malaria mortality in 2020, and potentially lead to even greater increases in subsequent years. To avoid a reversal of two decades of progress against malaria, averting this public health disaster must remain an integrated priority alongside the response to COVID-19. Funding Bill and Melinda Gates Foundation; Channel 7 Telethon Trust, Western Australia.

Access to healthcare is a requirement for human well-being that is constrained, in part, by the allocation of healthcare resources relative to the geographically dispersed human population(1-3). Quantifying access to care globally is challenging due to the absence of a comprehensive database of healthcare facilities. We harness major data collection efforts underway by OpenStreetMap, Google Maps and academic researchers to compile the most complete collection of facility locations to date. Leveraging the geographically variable strengths of our facility datasets, we use an established methodology(4)to characterize travel time to healthcare facilities in unprecedented detail. We produce maps of travel time with and without access to motorized transport, thus characterizing travel time to healthcare for populations distributed across the wealth spectrum. We find that just 8.9% of the global population (646 million people) cannot reach healthcare within one hour if they have access to motorized transport, and that 43.3% (3.16 billion people) cannot reach a healthcare facility by foot within one hour. Our maps highlight an additional vulnerability faced by poorer individuals in remote areas and can help to estimate whether individuals will seek healthcare when it is needed, as well as providing an evidence base for efficiently distributing limited healthcare and transportation resources to underserved populations both now and in the future. A global analysis generating high-resolution maps of travel time shows that 91.1% of the world's population can reach a hospital or clinic within an hour if they have access to motorized transportation, but only 56.7% can do so by walking, highlighting additional inequities for underserved populations accessing healthcare.

Malaria transmission in Madagascar is highly heterogeneous, exhibiting spatial, seasonal and long-term trends. Previous efforts to map malaria risk in Madagascar used prevalence data from Malaria Indicator Surveys. These cross-sectional surveys, conducted during the high transmission season most recently in 2013 and 2016, provide nationally representative prevalence data but cover relatively short time frames. Conversely, monthly case data are collected at health facilities but suffer from biases, including incomplete reporting and low rates of treatment seeking. We combined survey and case data to make monthly maps of prevalence between 2013 and 2016. Health facility catchment populations were estimated to produce incidence rates from the case data. Smoothed incidence surfaces, environmental and socioeconomic covariates, and survey data informed a Bayesian prevalence model, in which a flexible incidence-to-prevalence relationship was learned. Modelled spatial trends were consistent over time, with highest prevalence in the coastal regions and low prevalence in the highlands and desert south. Prevalence was lowest in 2014 and peaked in 2015 and seasonality was widely observed, including in some lower transmission regions. These trends highlight the utility of monthly prevalence estimates over the four year period. By combining survey and case data using this two-step modelling approach, we were able to take advantage of the relative strengths of each metric while accounting for potential bias in the case data. Similar modelling approaches combining large datasets of different malaria metrics may be applicable across sub-Saharan Africa.

Background Many malaria-endemic areas experience seasonal fluctuations in case incidence as Anopheles mosquito and Plasmodium parasite life cycles respond to changing environmental conditions. Identifying location-specific seasonality characteristics is useful for planning interventions. While most existing maps of malaria seasonality use fixed thresholds of rainfall, temperature, and/or vegetation indices to identify suitable transmission months, we construct a statistical modelling framework for characterising the seasonal patterns derived directly from monthly health facility data. Methods With data from 2669 of the 3247 health facilities in Madagascar, a spatiotemporal regression model was used to estimate seasonal patterns across the island. In the absence of catchment population estimates or the ability to aggregate to the district level, this focused on the monthly proportions of total annual cases by health facility level. The model was informed by dynamic environmental covariates known to directly influence seasonal malaria trends. To identify operationally relevant characteristics such as the transmission start months and associated uncertainty measures, an algorithm was developed and applied to model realisations. A seasonality index was used to incorporate burden information from household prevalence surveys and summarise ‘how seasonal’ locations are relative to their surroundings. Results Positive associations were detected between monthly case proportions and temporally lagged covariates of rainfall and temperature suitability. Consistent with the existing literature, model estimates indicate that while most parts of Madagascar experience peaks in malaria transmission near March–April, the eastern coast experiences an earlier peak around February. Transmission was estimated to start in southeast districts before southwest districts, suggesting that indoor residual spraying should be completed in the same order. In regions where the data suggested conflicting seasonal signals or two transmission seasons, estimates of seasonal features had larger deviations and therefore less certainty. Conclusions Monthly health facility data can be used to establish seasonal patterns in malaria burden and augment the information provided by household prevalence surveys. The proposed modelling framework allows for evidence-based and cohesive inferences on location-specific seasonal characteristics. As health surveillance systems continue to improve, it is hoped that more of such data will be available to improve our understanding and planning of intervention strategies.

The economic and man-made resources that sustain human wellbeing are not distributed evenly across the world, but are instead heavily concentrated in cities. Poor access to opportunities and services offered by urban centres (a function of distance, transport infrastructure, and the spatial distribution of cities) is a major barrier to improved livelihoods and overall development. Advancing accessibility worldwide underpins the equity agenda of ‘leaving no one behind’ established by the Sustainable Development Goals of the United Nations1. This has renewed international efforts to accurately measure accessibility and generate a metric that can inform the design and implementation of development policies. The only previous attempt to reliably map accessibility worldwide, which was published nearly a decade ago2, predated the baseline for the Sustainable Development Goals and excluded the recent expansion in infrastructure networks, particularly in lower-resource settings. In parallel, new data sources provided by Open Street Map and Google now capture transportation networks with unprecedented detail and precision. Here we develop and validate a map that quantifies travel time to cities for 2015 at a spatial resolution of approximately one by one kilometre by integrating ten global-scale surfaces that characterize factors affecting human movement rates and 13,840 high-density urban centres within an established geospatial-modelling framework. Our results highlight disparities in accessibility relative to wealth as 50.9% of individuals living in low-income settings (concentrated in sub-Saharan Africa) reside within an hour of a city compared to 90.7% of individuals in high-income settings. By further triangulating this map against socioeconomic datasets, we demonstrate how access to urban centres stratifies the economic, educational, and health status of humanity.

Background Indoor residual spraying (IRS) is a key tool for controlling and eliminating malaria by targeting vectors. To support the development of effective intervention strategies it is important to understand the impact of vector control tools on malaria incidence and on the spread of insecticide resistance. In 2006, the World Health Organization (WHO) stated that countries should report on coverage and impact of IRS, yet IRS coverage data are still sparse and unspecific. Here, the subnational coverage of IRS across sub-Saharan Africa for the four main insecticide classes from 1997 to 2017 were estimated. Methods Data on IRS deployment were collated from a variety of sources, including the President’s Malaria Initiative spray reports and National Malaria Control Programme reports, for all 46 malaria-endemic countries in sub-Saharan Africa from 1997 to 2017. The data were mapped to the applicable administrative divisions and the proportion of households sprayed for each of the four main insecticide classes; carbamates, organochlorines, organophosphates and pyrethroids was calculated. Results The number of countries implementing IRS increased considerably over time, although the focal nature of deployment means the number of people protected remains low. From 1997 to 2010, DDT and pyrethroids were commonly used, then partly replaced by carbamates from 2011 and by organophosphates from 2013. IRS deployment since the publication of resistance management guidelines has typically avoided overlap between pyrethroid IRS and ITN use. However, annual rotations of insecticide classes with differing modes of action are not routinely used. Conclusion This study highlights the gaps between policy and practice, emphasizing the continuing potential of IRS to drive resistance. The data presented here can improve studies on the impact of IRS on malaria incidence and help to guide future malaria control efforts.

Background: Since 2000, the scale-up of malaria control interventions has substantially reduced morbidity and mortality caused by the disease globally, fuelling bold aims for disease elimination. In tandem with increased availability of geospatially resolved data, malaria control programmes increasingly use high-resolution maps to characterise spatially heterogeneous patterns of disease risk and thus efficiently target areas of high burden. Methods: We updated and refined the Plasmodium falciparum parasite rate and clinical incidence models for sub-Saharan Africa, which rely on cross-sectional survey data for parasite rate and intervention coverage. For malaria endemic countries outside of sub-Saharan Africa, we produced estimates of parasite rate and incidence by applying an ecological downscaling approach to malaria incidence data acquired via routine surveillance. Mortality estimates were derived by linking incidence to systematically derived vital registration and verbal autopsy data. Informed by high-resolution covariate surfaces, we estimated P falciparum parasite rate, clinical incidence, and mortality at national, subnational, and 5 × 5 km pixel scales with corresponding uncertainty metrics. Findings: We present the first global, high-resolution map of P falciparum malaria mortality and the first global prevalence and incidence maps since 2010. These results are combined with those for Plasmodium vivax (published separately) to form the malaria estimates for the Global Burden of Disease 2017 study. The P falciparum estimates span the period 2000–17, and illustrate the rapid decline in burden between 2005 and 2017, with incidence declining by 27·9% and mortality declining by 42·5%. Despite a growing population in endemic regions, P falciparum cases declined between 2005 and 2017, from 232·3 million (95% uncertainty interval 198·8–277·7) to 193·9 million (156·6–240·2) and deaths declined from 925 800 (596 900–1 341 100) to 618 700 (368 600–952 200). Despite the declines in burden, 90·1% of people within sub-Saharan Africa continue to reside in endemic areas, and this region accounted for 79·4% of cases and 87·6% of deaths in 2017. Interpretation: High-resolution maps of P falciparum provide a contemporary resource for informing global policy and malaria control planning, programme implementation, and monitoring initiatives. Amid progress in reducing global malaria burden, areas where incidence trends have plateaued or increased in the past 5 years underscore the fragility of hard-won gains against malaria. Efforts towards elimination should be strengthened in such areas, and those where burden remained high throughout the study period.

Background Malaria control has not been routinely informed by the assessment of subnational variation in malaria deaths. We combined data from the Malaria Atlas Project and the Global Burden of Disease Study to estimate malaria mortality across sub-Saharan Africa on a grid of 5 km(2) from 1990 through 2015. Methods We estimated malaria mortality using a spatiotemporal modeling framework of geolocated data (i.e., with known latitude and longitude) on the clinical incidence of malaria, coverage of antimalarial drug treatment, case fatality rate, and population distribution according to age. Results Across sub-Saharan Africa during the past 15 years, we estimated that there was an overall decrease of 57% (95% uncertainty interval, 46 to 65) in the rate of malaria deaths, from 12.5 (95% uncertainty interval, 8.3 to 17.0) per 10,000 population in 2000 to 5.4 (95% uncertainty interval, 3.4 to 7.9) in 2015. This led to an overall decrease of 37% (95% uncertainty interval, 36 to 39) in the number of malaria deaths annually, from 1,007,000 (95% uncertainty interval, 666,000 to 1,376,000) to 631,000 (95% uncertainty interval, 394,000 to 914,000). The share of malaria deaths among children younger than 5 years of age ranged from more than 80% at a rate of death of more than 25 per 10,000 to less than 40% at rates below 1 per 10,000. Areas with high malaria mortality (>10 per 10,000) and low coverage (