Search
Research
A malaria seasonality dataset for sub-Saharan AfricaMalaria imposes a significant global health burden and remains a major cause of child mortality in sub-Saharan Africa. In many countries, malaria transmission varies seasonally. The use of seasonally-deployed interventions is expanding, and the effectiveness of these control measures hinges on quantitative and geographically-specific characterisations of malaria seasonality.
Research
What Heterogeneities in Individual-level Mobility Are Lost During Aggregation? Leveraging GPS Logger Data to Understand Fine-scale and Aggregated Patterns of MobilityHuman 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.
Research
Comparative assessment of the human and animal health surveillance systems in Tanzania: Opportunities for an integrated one health surveillance platformGlobally, 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.
Research
A Maximum Entropy Model of the Distribution of Dengue Serotype in MexicoPathogen strain diversity is an important driver of the trajectory of epidemics. The role of bioclimatic factors on the spatial distribution of dengue virus serotypes has, however, not been previously studied. Hence, we developed municipality-scale environmental suitability maps for the four dengue virus serotypes using maximum entropy modeling.
Research
Malaria treatment for prevention: a modelling study of the impact of routine case management on malaria prevalence and burdenTesting and treating symptomatic malaria cases is crucial for case management, but it may also prevent future illness by reducing mean infection duration. Measuring the impact of effective treatment on burden and transmission via field studies or routine surveillance systems is difficult and potentially unethical. This project uses mathematical modeling to explore how increasing treatment of symptomatic cases impacts malaria prevalence and incidence.
Research
Patterns and trends of in-hospital mortality due to non-communicable diseases and injuries in Tanzania, 2006–2015Globally, non-communicable diseases (NCD) kill about 40 million people annually, with about three-quarters of the deaths occurring in low- and middle-income countries. This study was carried out to determine the patterns, trends, and causes of in-hospital non-communicable disease (NCD) and injury deaths in Tanzania from 2006-2015.
Research
Geospatial modelling for malaria risk stratification and intervention targeting for low-endemic countriesPunam Susan Tasmin Amratia Rumisha Symons PhD PhD (Biostatistics) Honorary Research Associate Honorary Research Associate Honorary Research Associate
Research
Mapping the endemicity and seasonality of clinical malaria for intervention targeting in Haiti using routine case dataTowards the goal of malaria elimination on Hispaniola, the National Malaria Control Program of Haiti and its international partner organisations are conducting a campaign of interventions targeted to high-risk communities prioritised through evidence-based planning. Here we present a key piece of this planning: an up-to-date, fine-scale endemicity map and seasonality profile for Haiti informed by monthly case counts.
Research
Reconstructing the early global dynamics of under-ascertained COVID-19 cases and infectionsAsymptomatic or subclinical SARS-CoV-2 infections are often unreported, which means that confirmed case counts may not accurately reflect underlying epidemic dynamics. Understanding the level of ascertainment (the ratio of confirmed symptomatic cases to the true number of symptomatic individuals) and undetected epidemic progression is crucial to informing COVID-19 response planning, including the introduction and relaxation of control measures.
Research
Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventionsSince 2004, malaria transmission on Bioko Island has declined significantly as a result of the scaling-up of control interventions. The aim of eliminating malaria from the Island remains elusive, however, underscoring the need to adapt control to the local context. Understanding the factors driving the risk of malaria infection is critical to inform optimal suits of interventions in this adaptive approach.