Explore the vast range of titles available.

During the Millennium Development Goal (MDG) era, many countries in Africa achieved marked reductions in under-5 and neonatal mortality. Yet the pace of progress toward these goals substantially varied at the national level, demonstrating an essential need for tracking even more local trends in child mortality. With the adoption of the Sustainable Development Goals (SDGs) in 2015, which established ambitious targets for improving child survival by 2030, optimal intervention planning and targeting will require understanding of trends and rates of progress at a higher spatial resolution. In this study, we aimed to generate high-resolution estimates of under-5 and neonatal all-cause mortality across 46 countries in Africa. We assembled 235 geographically resolved household survey and census data sources on child deaths to produce estimates of under-5 and neonatal mortality at a resolution of 5 × 5 km grid cells across 46 African countries for 2000, 2005, 2010, and 2015. We used a Bayesian geostatistical analytical framework to generate these estimates, and implemented predictive validity tests. In addition to reporting 5 × 5 km estimates, we also aggregated results obtained from these estimates into three different levels—national, and subnational administrative levels 1 and 2—to provide the full range of geospatial resolution that local, national, and global decision makers might require. Amid improving child survival in Africa, there was substantial heterogeneity in absolute levels of under-5 and neonatal mortality in 2015, as well as the annualised rates of decline achieved from 2000 to 2015. Subnational areas in countries such as Botswana, Rwanda, and Ethiopia recorded some of the largest decreases in child mortality rates since 2000, positioning them well to achieve SDG targets by 2030 or earlier. Yet these places were the exception for Africa, since many areas, particularly in central and western Africa, must reduce under-5 mortality rates by at least 8·8% per year, between 2015 and 2030, to achieve the SDG 3.2 target for under-5 mortality by 2030. In the absence of unprecedented political commitment, financial support, and medical advances, the viability of SDG 3.2 achievement in Africa is precarious at best. By producing under-5 and neonatal mortality rates at multiple levels of geospatial resolution over time, this study provides key information for decision makers to target interventions at populations in the greatest need. In an era when precision public health increasingly has the potential to transform the design, implementation, and impact of health programmes, our 5 × 5 km estimates of child mortality in Africa provide a baseline against which local, national, and global stakeholders can map the pathways for ending preventable child deaths by 2030. Bill & Melinda Gates Foundation.

Background Antimicrobial resistance (AMR) is an increasing threat to global health. There are > 14 million cases of enteric fever every year and > 135,000 deaths. The disease is primarily controlled by antimicrobial treatment, but this is becoming increasingly difficult due to AMR. Our objectives were to assess the prevalence and geographic distribution of AMR in Salmonella enterica serovars Typhi and Paratyphi A infections globally, to evaluate the extent of the problem, and to facilitate the creation of geospatial maps of AMR prevalence to help targeted public health intervention. Methods We performed a systematic review of the literature by searching seven databases for studies published between 1990 and 2018. We recategorised isolates to allow the analysis of fluoroquinolone resistance trends over the study period. The prevalence of multidrug resistance (MDR) and fluoroquinolone non-susceptibility (FQNS) in individual studies was illustrated by forest plots, and a random effects meta-analysis was performed, stratified by Global Burden of Disease (GBD) region and 5-year time period. Heterogeneity was assessed using the I 2 statistics. We present a descriptive analysis of ceftriaxone and azithromycin resistance. Findings We identified 4557 articles, of which 384, comprising 124,347 isolates (94,616 S . Typhi and 29,731 S . Paratyphi A) met the pre-specified inclusion criteria. The majority (276/384; 72%) of studies were from South Asia; 40 (10%) articles were identified from Sub-Saharan Africa. With the exception of MDR S . Typhi in South Asia, which declined between 1990 and 2018, and MDR S . Paratyphi A, which remained at low levels, resistance trends worsened for all antimicrobials in all regions. We identified several data gaps in Africa and the Middle East. Incomplete reporting of antimicrobial susceptibility testing (AST) and lack of quality assurance were identified. Interpretation Drug-resistant enteric fever is widespread in low- and middle-income countries, and the situation is worsening. It is essential that public health and clinical measures, which include improvements in water quality and sanitation, the deployment of S . Typhi vaccination, and an informed choice of treatment are implemented. However, there is no licenced vaccine for S . Paratyphi A. The standardised reporting of AST data and rollout of external quality control assessment are urgently needed to facilitate evidence-based policy and practice. Trial registration PROSPERO CRD42018029432 .

Substantial outbreaks of yellow fever in Angola and Brazil in the past 2 years, combined with global shortages in vaccine stockpiles, highlight a pressing need to assess present control strategies. The aims of this study were to estimate global yellow fever vaccination coverage from 1970 through to 2016 at high spatial resolution and to calculate the number of individuals still requiring vaccination to reach population coverage thresholds for outbreak prevention. For this adjusted retrospective analysis, we compiled data from a range of sources (eg, WHO reports and health-service-provider registeries) reporting on yellow fever vaccination activities between May 1, 1939, and Oct 29, 2016. To account for uncertainty in how vaccine campaigns were targeted, we calculated three population coverage values to encompass alternative scenarios. We combined these data with demographic information and tracked vaccination coverage through time to estimate the proportion of the population who had ever received a yellow fever vaccine for each second level administrative division across countries at risk of yellow fever virus transmission from 1970 to 2016. Overall, substantial increases in vaccine coverage have occurred since 1970, but notable gaps still exist in contemporary coverage within yellow fever risk zones. We estimate that between 393·7 million and 472·9 million people still require vaccination in areas at risk of yellow fever virus transmission to achieve the 80% population coverage threshold recommended by WHO; this represents between 43% and 52% of the population within yellow fever risk zones, compared with between 66% and 76% of the population who would have required vaccination in 1970. Our results highlight important gaps in yellow fever vaccination coverage, can contribute to improved quantification of outbreak risk, and help to guide planning of future vaccination efforts and emergency stockpiling. The Rhodes Trust, Bill & Melinda Gates Foundation, the Wellcome Trust, the National Library of Medicine of the National Institutes of Health, the European Union's Horizon 2020 research and innovation programme.

Background Climate change is predicted to impact the transmission dynamics of vector-borne diseases. Tsetse flies ( Glossina ) transmit species of Trypanosoma that cause human and animal African trypanosomiasis. A previous modelling study showed that temperature increases between 1990 and 2017 can explain the observed decline in abundance of tsetse at a single site in the Mana Pools National Park of Zimbabwe. Here, we apply a mechanistic model of tsetse population dynamics to predict how increases in temperature may have changed the distribution and relative abundance of Glossina pallidipes across northern Zimbabwe. Methods Local weather station temperature measurements were previously used to fit the mechanistic model to longitudinal G. pallidipes catch data. To extend the use of the model, we converted MODIS land surface temperature to air temperature, compared the converted temperatures with available weather station data to confirm they aligned, and then re-fitted the mechanistic model using G. pallidipes catch data and air temperature estimates. We projected this fitted model across northern Zimbabwe, using simulations at a 1 km × 1 km spatial resolution, between 2000 to 2016. Results We produced estimates of relative changes in G. pallidipes mortality, larviposition, emergence rates and abundance, for northern Zimbabwe. Our model predicts decreasing tsetse populations within low elevation areas in response to increasing temperature trends during 2000–2016. Conversely, we show that high elevation areas (> 1000 m above sea level), previously considered too cold to sustain tsetse, may now be climatically suitable. Conclusions To our knowledge, the results of this research represent the first regional-scale assessment of temperature related tsetse population dynamics, and the first high spatial-resolution estimates of this metric for northern Zimbabwe. Our results suggest that tsetse abundance may have declined across much of the Zambezi Valley in response to changing climatic conditions during the study period. Future research including empirical studies is planned to improve model accuracy and validate predictions for other field sites in Zimbabwe.

Malaria in sub-Saharan Africa has historically been almost exclusively attributed to Plasmodium falciparum (Pf). Current diagnostic and surveillance systems in much of sub-Saharan Africa are not designed to identify or report non-Pf human malaria infections accurately, resulting in a dearth of routine epidemiological data about their significance. The high prevalence of Duffy negativity provided a rationale for excluding the possibility of Plasmodium vivax (Pv) transmission. However, review of varied evidence sources including traveller infections, community prevalence surveys, local clinical case reports, entomological and serological studies contradicts this viewpoint. Here, these data reports are weighted in a unified framework to reflect the strength of evidence of indigenous Pv transmission in terms of diagnostic specificity, size of individual reports and corroboration between evidence sources. Direct evidence was reported from 21 of the 47 malaria-endemic countries studied, while 42 countries were attributed with infections of visiting travellers. Overall, moderate to conclusive evidence of transmission was available from 18 countries, distributed across all parts of the continent. Approximately 86.6 million Duffy positive hosts were at risk of infection in Africa in 2015. Analysis of the mechanisms sustaining Pv transmission across this continent of low frequency of susceptible hosts found that reports of Pv prevalence were consistent with transmission being potentially limited to Duffy positive populations. Finally, reports of apparent Duffy-independent transmission are discussed. While Pv is evidently not a major malaria parasite across most of sub-Saharan Africa, the evidence presented here highlights its widespread low-level endemicity. An increased awareness of Pv as a potential malaria parasite, coupled with policy shifts towards species-specific diagnostics and reporting, will allow a robust assessment of the public health significance of Pv, as well as the other neglected non-Pf parasites, which are currently invisible to most public health authorities in Africa, but which can cause severe clinical illness and require specific control interventions.

Surveillance is an essential component of global programs to eliminate infectious diseases and avert epidemics of (re-)emerging diseases. As the numbers of cases decline, costs of treatment and control diminish but those for surveillance remain high even after the 'last' case. Reducing surveillance may risk missing persistent or (re-)emerging foci of disease. Here, we use a simulation-based approach to determine the minimal number of passive surveillance sites required to ensure maximum coverage of a population at-risk (PAR) of an infectious disease. For this study, we use Gambian human African trypanosomiasis (g-HAT) in north-western Uganda, a neglected tropical disease (NTD) which has been reduced to historically low levels (<1000 cases/year globally), as an example. To quantify travel time to diagnostic facilities, a proxy for surveillance coverage, we produced a high spatial-resolution resistance surface and performed cost-distance analyses. We simulated travel time for the PAR with different numbers (1-170) and locations (170,000 total placement combinations) of diagnostic facilities, quantifying the percentage of the PAR within 1h and 5h travel of the facilities, as per in-country targets. Our simulations indicate that a 70% reduction (51/170) in diagnostic centres still exceeded minimal targets of coverage even for remote populations, with >95% of a total PAR of ~3million individuals living ≤1h from a diagnostic centre, and we demonstrate an approach to best place these facilities, informing a minimal impact scale back. Our results highlight that surveillance of g-HAT in north-western Uganda can be scaled back without substantially reducing coverage of the PAR. The methodology described can contribute to cost-effective and equable strategies for the surveillance of NTDs and other infectious diseases approaching elimination or (re-)emergence.

Background Tsetse flies (Glossina) transmit Trypanosoma brucei gambiense which causes Gambian human African trypanosomiasis (gHAT) in Central and West Africa. Several countries use Tiny Targets, comprising insecticide-treated panels of material which attract and kill tsetse, as part of their national programmes to eliminate gHAT. We studied how the scale and arrangement of target deployment affected the efficacy of control. Methodology and principal findings Between 2012 and 2016, Tiny Targets were deployed biannually along the larger rivers of Arua, Maracha, Koboko and Yumbe districts in North West Uganda with the aim of reducing the abundance of tsetse to interrupt transmission. The extent of these deployments increased from ~250 km.sup.2 in 2012 to ~1600 km.sup.2 in 2015. The impact of Tiny Targets on tsetse population was assessed by analysing catches of tsetse from a network of monitoring traps; sub-samples of captured tsetse were dissected to estimate their age and infection status. In addition, the condition of 780 targets (~195/district) was assessed for up to six months after deployment. In each district, mean daily catches of tsetse (G. fuscipes fuscipes) from monitoring traps declined significantly by >80% following the deployment of targets. The reduction was apparent for several kilometres on adjacent lengths of the same river but not in other rivers a kilometre or so away. Expansion of the operational area did not always produce higher levels of suppression or detectable change in the age structure or infection rates of the population, perhaps due to the failure to treat the smaller streams and/or invasion from adjacent untreated areas. The median effective life of a Tiny Target was 61 (41.8-80.2, 95% CI) days. Conclusions Scaling-up of tsetse control reduced the population of tsetse by >80% across the intervention area. Even better control might be achievable by tackling invasion of flies from infested areas within and outside the current intervention area. This might involve deploying more targets, especially along smaller rivers, and extending the effective life of Tiny Targets.

Background Japanese encephalitis (JE) is one of the most significant aetiological agents of viral encephalitis in Asia. This medically important arbovirus is primarily spread from vertebrate hosts to humans by the mosquito vector Culex tritaeniorhynchus . Knowledge of the contemporary distribution of this vector species is lacking, and efforts to define areas of disease risk greatly depend on a thorough understanding of the variation in this mosquito’s geographical distribution. Results We assembled a contemporary database of Cx. tritaeniorhynchus presence records within Japanese encephalitis risk areas from formal literature and other relevant resources, resulting in 1,045 geo-referenced, spatially and temporally unique presence records spanning from 1928 to 2014 (71.9% of records obtained between 2001 and 2014). These presence data were combined with a background dataset capturing sample bias in our presence dataset, along with environmental and socio-economic covariates, to inform a boosted regression tree model predicting environmental suitability for Cx. tritaeniorhynchus at each 5 × 5 km gridded cell within areas of JE risk. The resulting fine-scale map highlights areas of high environmental suitability for this species across India, Nepal and China that coincide with areas of high JE incidence, emphasising the role of this vector in disease transmission and the utility of the map generated. Conclusions Our map contributes towards efforts determining the spatial heterogeneity in Cx. tritaeniorhynchus distribution within the limits of JE transmission. Specifically, this map can be used to inform vector control programs and can be used to identify key areas where the prevention of Cx. tritaeniorhynchus establishment should be a priority.

Vector-borne diseases are important causes of mortality and morbidity in humans and livestock, particularly for poorer communities and countries in the tropics. Large-scale programs against these diseases, for example malaria, dengue and African trypanosomiasis, include vector control, and assessing the impact of this intervention requires frequent and extensive monitoring of disease vector abundance. Such monitoring can be expensive, especially in the later stages of a successful program where numbers of vectors and cases are low. We developed a system that allows the identification of monitoring sites where pre-intervention densities of vectors are predicted to be high, and travel cost to sites is low, highlighting the most efficient locations for longitudinal monitoring. Using remotely sensed imagery and an image classification algorithm, we mapped landscape resistance associated with on- and off-road travel for every gridded location (3m and 0.5m grid cells) within Koboko district, Uganda. We combine the accessibility surface with pre-existing estimates of tsetse abundance and propose a stratified sampling approach to determine the most efficient locations for longitudinal data collection. Our modelled predictions were validated against empirical measurements of travel-time and existing maps of road networks. We applied this approach in northern Uganda where a large-scale vector control program is being implemented to control human African trypanosomiasis, a neglected tropical disease (NTD) caused by trypanosomes transmitted by tsetse flies. Our accessibility surfaces indicate a high performance when compared to empirical data, with remote sensing identifying a further ~70% of roads than existing networks. By integrating such estimates with predictions of tsetse abundance, we propose a methodology to determine the optimal placement of sentinel monitoring sites for evaluating control programme efficacy, moving from a nuanced, ad-hoc approach incorporating intuition, knowledge of vector ecology and local knowledge of geographic accessibility, to a reproducible, quantifiable one.

Background Riverine species of tsetse ( Glossina ) transmit Trypanosoma brucei gambiense , which causes Gambian human African trypanosomiasis (gHAT), a neglected tropical disease. Uganda aims to eliminate gHAT as a public health problem through detection and treatment of human cases and vector control. The latter is being achieved through the deployment of ‘Tiny Targets’, insecticide-impregnated panels of material which attract and kill tsetse. We analysed the spatial and temporal distribution of cases of gHAT in Uganda during the period 2010–2019 to assess whether Tiny Targets have had an impact on disease incidence. Methods To quantify the deployment of Tiny Targets, we mapped the rivers and their associated watersheds in the intervention area. We then categorised each of these on a scale of 0–3 according to whether Tiny Targets were absent (0), present only in neighbouring watersheds (1), present in the watersheds but not all neighbours (2), or present in the watershed and all neighbours (3). We overlaid all cases that were diagnosed between 2000 and 2020 and assessed whether the probability of finding cases in a watershed changed following the deployment of targets. We also estimated the number of cases averted through tsetse control. Results We found that following the deployment of Tiny Targets in a watershed, there were fewer cases of HAT, with a sampled error probability of 0.007. We estimate that during the intervention period 2012–2019 we should have expected 48 cases (95% confidence intervals = 40–57) compared to the 36 cases observed. The results are robust to a range of sensitivity analyses. Conclusions Tiny Targets have reduced the incidence of gHAT by 25% in north-western Uganda. Graphical abstract