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As both mechanistic and geospatial malaria modeling methods become more integrated into malaria policy decisions, there is increasing demand for strategies that combine these two methods. This paper introduces a novel archetypes-based methodology for generating high-resolution intervention impact maps based on mechanistic model simulations. An example configuration of the framework is described and explored.
Children recovering from severe malarial anaemia (SMA) remain at high risk of readmission and death after discharge from hospital. However, a recent trial found that post-discharge malaria chemoprevention (PDMC) with dihydroartemisinin-piperaquine reduces this risk. We developed a mathematical model describing the daily incidence of uncomplicated and severe malaria requiring readmission among 0-5-year old children after hospitalised SMA.
An effective disease surveillance system is critical for early detection and response to disease epidemics. This study aimed to assess the capacity to manage and utilize disease surveillance data and implement an intervention to improve data analysis and use at the district level in Tanzania.
Human movement drives spatial transmission patterns of infectious diseases. Population-level mobility patterns are often quantified using aggregated data sets, such as census migration surveys or mobile phone data. These data are often unable to quantify individual-level travel patterns and lack the information needed to discern how mobility varies by demographic groups. Individual-level datasets can capture additional, more precise, aspects of mobility that may impact disease risk or transmission patterns and determine how mobility differs across cohorts; however, these data are rare, particularly in locations such as sub-Saharan Africa.
The intensity of transmission of Aedes-borne viruses is heterogeneous, and multiple factors can contribute to variation at small spatial scales. Illuminating drivers of heterogeneity in prevalence over time and space would provide information for public health authorities. The objective of this study is to detect the spatiotemporal clusters and determine the risk factors of three major Aedes-borne diseases, Chikungunya virus, Dengue virus, and Zika virus clusters in Mexico.
Undernutrition is a major risk factor for tuberculosis (TB), which is estimated to be responsible for 1.9 million TB cases per year globally. The effectiveness of micronutrient supplementation on TB treatment outcomes and its prognostic markers (sputum conversion, serum zinc, retinol and haemoglobin levels) has been poorly understood.
Childhood obesity and physical inactivity are two of the most significant modifiable risk factors for the prevention of non-communicable diseases. Yet, a third of children in Wales and Australia are overweight or obese, and only 20% of UK and Australian children are sufficiently active.
The economic and social development of nations relies on their population having physical access to services and employment opportunities. For the vast majority of the 3.4 billion people living in rural areas, this largely depends on their access to urban centers of different sizes.
Globally, there have been calls for an integrated zoonotic disease surveillance system. This study aimed to assess human and animal health surveillance systems to identify opportunities for One Health surveillance platform in Tanzania.
The spatial and temporal variability inherent in malaria transmission within countries implies that targeted interventions for malaria control in high-burden settings and subnational elimination are a practical necessity. Identifying the spatio-temporal incidence, risk, and trends at different administrative geographies within malaria-endemic countries and monitoring them in near real-time as change occurs is crucial for developing and introducing cost-effective, subnational control and elimination intervention strategies.