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A random effects meta-analysis was used to estimate the pooled prevalence of HIV infection within minority indigenous populations of the South-East Asia (SEAR) and Western Pacific Regions (WPR). Sub-group analyses were conducted, and the sources of heterogeneity explored through meta-regression. The majority of studies were undertaken in high HIV risk subpopulations.
Access to medical treatment for fever is essential to prevent morbidity and mortality in individuals and to prevent transmission of communicable febrile illness in communities. Quantification of the rates at which treatment is accessed is critical for health system planning and a prerequisite for disease burden estimates.
Reliable and detailed data on the prevalence of tuberculosis (TB) with sub-national estimates are scarce in Ethiopia. We address this knowledge gap by spatially predicting the national, sub-national and local prevalence of TB, and identifying drivers of TB prevalence across the country.
Despite significant decline in the past two decades, malaria is still a major public health concern in Tanzania; with over 93% of the population still at risk. Community knowledge, attitudes and practices, and beliefs are key in enhancing uptake and utilization of malaria control interventions, but there is a lack of information on their contribution to effective control of the disease.
Low socioeconomic status (SES), high temperature, and increasing rainfall patterns are associated with increased dengue case counts. However, the effect of climatic variables on individual dengue virus (DENV) serotypes and the extent to which serotype count affects the rate of severe dengue in Mexico have not been studied before.
There has been a limited understanding of the longitudinal trajectory and determinants of socio-emotional outcomes among children in out-of-home care (OOHC). This study aimed to examine child socio-demographics, pre-care maltreatment, placement, and caregiver factors associated with trajectories of socio-emotional difficulties of children in OOHC.
The impacts of the COVID-19 pandemic have been vast and are not limited to physical health. Many adolescents have experienced disruptions to daily life, including changes in their school routine and family’s financial or emotional security, potentially impacting their emotional wellbeing.
By mapping land use under projections of socio-economic change, ecological changes can be predicted to inform conservation decision-making. We present a land use model that enables the fine-scale mapping of land use change under future scenarios. Its predictions can be used as input to virtually all existing spatially-explicit ecological models.
Due to global climate change–induced shifts in species distributions, estimating changes in community composition through the use of Species Distribution Models has become a key management tool. Being able to determine how species associations change along environmental gradients is likely to be pivotal in exploring the magnitude of future changes in species’ distributions.
Individual-based models have become important tools in the global battle against infectious diseases, yet model complexity can make calibration to biological and epidemiological data challenging. We propose using a Bayesian optimization framework employing Gaussian process or machine learning emulator functions to calibrate a complex malaria transmission simulator.