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Scrub typhus, a miteborne rickettsiosis, has emerged in many areas globally. We analyzed the incidence and spatial-temporal distribution of scrub typhus in China during 1952-1989 and 2006-2016 using national disease surveillance data. A total of 133,623 cases and 174 deaths were recorded. The average annual incidence was 0.13 cases/100,000 population during 1952-1989; incidence increased sharply from 0.09/100,000 population in 2006 to 1.60/100,000 population in 2016. The disease, historically endemic to southern China, has expanded to all the provinces across both rural and urban areas. We identified 3 distinct seasonal patterns nationwide; infections peaked in summer in the southwest, summer-autumn in the southeast, and autumn in the middle-east. Persons >40 years of age and in nonfarming occupations had a higher risk for death. The changing epidemiology of scrub typhus in China warrants an enhanced disease control and prevention program.

Dengue is a mosquito-borne viral infection that has spread throughout the tropical world over the past 60 years and now affects over half the world’s population. The geographical range of dengue is expected to further expand due to ongoing global phenomena including climate change and urbanization. We applied statistical mapping techniques to the most extensive database of case locations to date to predict global environmental suitability for the virus as of 2015. We then made use of climate, population and socioeconomic projections for the years 2020, 2050 and 2080 to project future changes in virus suitability and human population at risk. This study is the first to consider the spread of Aedes mosquito vectors to project dengue suitability. Our projections provide a key missing piece of evidence for the changing global threat of vector-borne disease and will help decision-makers worldwide to better prepare for and respond to future changes in dengue risk. Statistical mapping techniques provide insights into the current geographical spread of the mosquito-borne dengue virus infection and predict changes in the areas that will be environmentally suitable to the virus for the years 2020, 2050 and 2080.

Background The host, microbial, and environmental factors that contribute to variation in tuberculosis (TB) disease are incompletely understood. Accumulating evidence suggests that one driver of geographic variation in TB disease is the local ecology of mycobacterial genotypes or strains, and there is a need for a comprehensive and systematic synthesis of these data. The objectives of this study were to (1) map the global distribution of genotypes that cause TB disease and (2) examine whether any epidemiologically relevant clinical characteristics were associated with those genotypes. Methods We performed a systematic review of PubMed and Scopus to create a comprehensive dataset of human TB molecular epidemiology studies that used representative sampling techniques. The methods were developed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). We extracted and synthesized data from studies that reported prevalence of bacterial genotypes and from studies that reported clinical characteristics associated with those genotypes. Results The results of this study are twofold. First, we identified 206 studies for inclusion in the study, representing over 200,000 bacterial isolates collected over 27 years in 85 countries. We mapped the genotypes and found that, consistent with previously published maps, Euro-American lineage 4 and East Asian lineage 2 strains are widespread, and West African lineages 5 and 6 strains are geographically restricted. Second, 30 studies also reported transmission chains and 4 reported treatment failure associated with genotypes. We performed a meta-analysis and found substantial heterogeneity across studies. However, based on the data available, we found that lineage 2 strains may be associated with increased risk of transmission chains, while lineages 5 and 6 strains may be associated with reduced risk, compared with lineage 4 strains. Conclusions This study provides the most comprehensive systematic analysis of the evidence for diversity in bacterial strains that cause TB disease. The results show both geographic and epidemiological differences between strains, which could inform our understanding of the global burden of TB. Our findings also highlight the challenges of collecting the clinical data required to inform TB diagnosis and treatment. We urge future national TB programs and research efforts to prioritize and reinforce clinical data collection in study designs and results dissemination.

Snakebite envenoming is a frequently overlooked cause of mortality and morbidity. Data for snake ecology and existing snakebite interventions are scarce, limiting accurate burden estimation initiatives. Low global awareness stunts new interventions, adequate health resources, and available health care. Therefore, we aimed to synthesise currently available data to identify the most vulnerable populations at risk of snakebite, and where additional data to manage this global problem are needed. We assembled a list of snake species using WHO guidelines. Where relevant, we obtained expert opinion range (EOR) maps from WHO or the Clinical Toxinology Resources. We also obtained occurrence data for each snake species from a variety of websites, such as VertNet and iNaturalist, using the spocc R package (version 0.7.0). We removed duplicate occurrence data and categorised snakes into three groups: group A (no available EOR map or species occurrence records), group B (EOR map but <5 species occurrence records), and group C (EOR map and ≥5 species occurrence records). For group C species, we did a multivariate environmental similarity analysis using the 2008 WHO EOR maps and newly available evidence. Using these data and the EOR maps, we produced contemporary range maps for medically important venomous snake species at a 5 × 5 km resolution. We subsequently triangulated these data with three health system metrics (antivenom availability, accessibility to urban centres, and the Healthcare Access and Quality [HAQ] Index) to identify the populations most vulnerable to snakebite morbidity and mortality. We provide a map showing the ranges of 278 snake species globally. Although about 6·85 billion people worldwide live within range of areas inhabited by snakes, about 146·70 million live within remote areas lacking quality health-care provisioning. Comparing opposite ends of the HAQ Index, 272·91 million individuals (65·25%) of the population within the lowest decile are at risk of exposure to any snake for which no effective therapy exists compared with 519·46 million individuals (27·79%) within the highest HAQ Index decile, showing a disproportionate coverage in reported antivenom availability. Antivenoms were available for 119 (43%) of 278 snake species evaluated by WHO, while globally 750·19 million (10·95%) of those living within snake ranges live more than 1 h from population centres. In total, we identify about 92·66 million people living within these vulnerable geographies, including many sub-Saharan countries, Indonesia, and other parts of southeast Asia. Identifying exact populations vulnerable to the most severe outcomes of snakebite envenoming at a subnational level is important for prioritising new data collection and collation, reinforcing envenoming treatment, existing health-care systems, and deploying currently available and future interventions. These maps can guide future research efforts on snakebite envenoming from both ecological and public health perspectives and better target future estimates of the burden of this neglected tropical disease. Bill & Melinda Gates Foundation.

Background Brazil has high burdens of tuberculosis (TB) and HIV, as previously estimated for the 26 states and the Federal District, as well as high levels of inequality in social and health indicators. We improved the geographic detail of burden estimation by modelling deaths due to TB and HIV and TB case fatality ratios for the more than 5400 municipalities in Brazil. Methods This ecological study used vital registration data from the national mortality information system and TB case notifications from the national communicable disease notification system from 2001 to 2015. Mortality due to TB and HIV was modelled separately by cause and sex using a Bayesian spatially explicit mixed effects regression model. TB incidence was modelled using the same approach. Results were calibrated to the Global Burden of Disease Study 2016. Case fatality ratios were calculated for TB. Results There was substantial inequality in TB and HIV mortality rates within the nation and within states. National-level TB mortality in people without HIV infection declined by nearly 50% during 2001 to 2015, but HIV mortality declined by just over 20% for males and 10% for females. TB and HIV mortality rates for municipalities in the 90th percentile nationally were more than three times rates in the 10th percentile, with nearly 70% of the worst-performing municipalities for male TB mortality and more than 75% for female mortality in 2001 also in the worst decile in 2015. The same municipality ranking metric for HIV was observed to be between 55% and 61%. Within states, the TB mortality rate ratios by sex for municipalities in the worst decile versus the best decile varied from 1.4 to 2.9, and HIV varied from 1.4 to 4.2. The World Health Organization target case fatality rate for TB of less than 10% was achieved in 9.6% of municipalities for males versus 38.4% for females in 2001 and improved to 38.4% and 56.6% of municipalities for males versus females, respectively, by 2014. Conclusions Mortality rates in municipalities within the same state exhibited nearly as much relative variation as within the nation as a whole. Monitoring the mortality burden at this level of geographic detail is critical for guiding precision public health responses.

Virtual focus groups-such as online chat and video groups-are increasingly promoted as qualitative research tools. Theoretically, virtual groups offer several advantages, including lower cost, faster recruitment, greater geographic diversity, enrollment of hard-to-reach populations, and reduced participant burden. However, no study has compared virtual and in-person focus groups on these metrics. To rigorously compare virtual and in-person focus groups on cost, recruitment, and participant logistics. We examined 3 focus group modes and instituted experimental controls to ensure a fair comparison. We conducted 6 1-hour focus groups in August 2014 using in-person (n=2), live chat (n=2), and video (n=2) modes with individuals who had type 2 diabetes (n=48 enrolled, n=39 completed). In planning groups, we solicited bids from 6 virtual platform vendors and 4 recruitment firms. We then selected 1 platform or facility per mode and a single recruitment firm across all modes. To minimize bias, the recruitment firm employed different recruiters by mode who were blinded to recruitment efforts for other modes. We tracked enrollment during a 2-week period. A single moderator conducted all groups using the same guide, which addressed the use of technology to communicate with health care providers. We conducted the groups at the same times of day on Monday to Wednesday during a single week. At the end of each group, participants completed a short survey. Virtual focus groups offered minimal cost savings compared with in-person groups (US $2000 per chat group vs US $2576 per in-person group vs US $2,750 per video group). Although virtual groups did not incur travel costs, they often had higher management fees and miscellaneous expenses (eg, participant webcams). Recruitment timing did not differ by mode, but show rates were higher for in-person groups (94% [15/16] in-person vs 81% [13/16] video vs 69% [11/16] chat). Virtual group participants were more geographically diverse (but with significant clustering around major metropolitan areas) and more likely to be non-white, less educated, and less healthy. Internet usage was higher among virtual group participants, yet virtual groups still reached light Internet users. In terms of burden, chat groups were easiest to join and required the least preparation (chat = 13 minutes, video = 40 minutes, in-person = 78 minutes). Virtual group participants joined using laptop or desktop computers, and most virtual participants (82% [9/11] chat vs 62% [8/13] video) reported having no other people in their immediate vicinity. Virtual focus groups offer potential advantages for participant diversity and reaching less healthy populations. However, virtual groups do not appear to cost less or recruit participants faster than in-person groups. Further research on virtual group data quality and group dynamics is needed to fully understand their advantages and limitations.

As Indonesia moves to provide health coverage for all citizens, understanding patterns of morbidity and mortality is important to allocate resources and address inequality. The Global Burden of Disease 2016 study (GBD 2016) estimates sources of early death and disability, which can inform policies to improve health care. We used GBD 2016 results for cause-specific deaths, years of life lost, years lived with disability, disability-adjusted life-years (DALYs), life expectancy at birth, healthy life expectancy, and risk factors for 333 causes in Indonesia and in seven comparator countries. Estimates were produced by location, year, age, and sex using methods outlined in GBD 2016. Using the Socio-demographic Index, we generated expected values for each metric and compared these against observed results. In Indonesia between 1990 and 2016, life expectancy increased by 8·0 years (95% uncertainty interval [UI] 7·3–8·8) to 71·7 years (71·0–72·3): the increase was 7·4 years (6·4–8·6) for males and 8·7 years (7·8–9·5) for females. Total DALYs due to communicable, maternal, neonatal, and nutritional causes decreased by 58·6% (95% UI 55·6–61·6), from 43·8 million (95% UI 41·4–46·5) to 18·1 million (16·8–19·6), whereas total DALYs from non-communicable diseases rose. DALYs due to injuries decreased, both in crude rates and in age-standardised rates. The three leading causes of DALYs in 2016 were ischaemic heart disease, cerebrovascular disease, and diabetes. Dietary risks were a leading contributor to the DALY burden, accounting for 13·6% (11·8–15·4) of DALYs in 2016. Over the past 27 years, health across many indicators has improved in Indonesia. Improvements are partly offset by rising deaths and a growing burden of non-communicable diseases. To maintain and increase health gains, further work is needed to identify successful interventions and improve health equity. The Bill & Melinda Gates Foundation.

Insufficient growth during childhood is associated with poor health outcomes and an increased risk of death. Between 2000 and 2015, nearly all African countries demonstrated improvements for children under 5 years old for stunting, wasting, and underweight, the core components of child growth failure. Here we show that striking subnational heterogeneity in levels and trends of child growth remains. If current rates of progress are sustained, many areas of Africa will meet the World Health Organization Global Targets 2025 to improve maternal, infant and young child nutrition, but high levels of growth failure will persist across the Sahel. At these rates, much, if not all of the continent will fail to meet the Sustainable Development Goal target—to end malnutrition by 2030. Geospatial estimates of child growth failure provide a baseline for measuring progress as well as a precision public health platform to target interventions to those populations with the greatest need, in order to reduce health disparities and accelerate progress. Geospatial estimates of child growth failure in Africa provide a baseline for measuring progress and a precision public health platform to target interventions to those populations with the greatest need. Mapping Africa's path to prosperity The UN's Sustainable Development Goals set a range of targets to improve global health and prosperity. Their success will rely on high-quality data to assess current progress and needs on a local scale. Simon Hay and colleagues study data gathered at the finest spatial scale yet of child growth and educational attainment across 51 African countries. The data show the spatiotemporal progression of these measures between 2000 and 2015 and reveal geographical inequalities. The authors use Bayesian-model-based geospatial mapping to estimate the prevalence of multiple outcomes related to child growth failure and educational inequality on a 5 kilometre by 5 kilometre scale, enabling them to estimate where various targets related to nutrition and educational attainment are more or less likely to be met.

Routine childhood vaccination is among the most cost-effective, successful public health interventions available. Amid substantial investments to expand vaccine delivery throughout Africa and strengthen administrative reporting systems, most countries still require robust measures of local routine vaccine coverage and changes in geographical inequalities over time. This analysis drew from 183 surveys done between 2000 and 2016, including data from 881 268 children in 49 African countries. We used a Bayesian geostatistical model calibrated to results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2017, to produce annual estimates with high-spatial resolution (5 ×    5 km) of diphtheria-pertussis-tetanus (DPT) vaccine coverage and dropout for children aged 12–23 months in 52 African countries from 2000 to 2016. Estimated third-dose (DPT3) coverage increased in 72·3% (95% uncertainty interval [UI] 64·6–80·3) of second-level administrative units in Africa from 2000 to 2016, but substantial geographical inequalities in DPT coverage remained across and within African countries. In 2016, DPT3 coverage at the second administrative (ie, district) level varied by more than 25% in 29 of 52 countries, with only two (Morocco and Rwanda) of 52 countries meeting the Global Vaccine Action Plan target of 80% DPT3 coverage or higher in all second-level administrative units with high confidence (posterior probability ≥95%). Large areas of low DPT3 coverage (≤50%) were identified in the Sahel, Somalia, eastern Ethiopia, and in Angola. Low first-dose (DPT1) coverage (≤50%) and high relative dropout (≥30%) together drove low DPT3 coverage across the Sahel, Somalia, eastern Ethiopia, Guinea, and Angola. Despite substantial progress in Africa, marked national and subnational inequalities in DPT coverage persist throughout the continent. These results can help identify areas of low coverage and vaccine delivery system vulnerabilities and can ultimately support more precise targeting of resources to improve vaccine coverage and health outcomes for African children. Bill & Melinda Gates Foundation.