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Understanding the temporal dynamics of mosquito populations underlying vector-borne disease transmission is key to optimizing control strategies. Many questions remain surrounding the drivers of these dynamics and how they vary between species-questions rarely answerable from individual entomological studies (that typically focus on a single location or species).
Infectious diseases have been shown to disproportionately affect indigenous populations. Tuberculosis (TB) and malaria continue to impose a significant burden on humanity and are among the infectious diseases targeted within the 2030 Agenda for Sustainable Development.
The COVID-19 pandemic has overwhelmed health systems in both developed and developing nations alike. Africa has one of the weakest health systems globally, but there is limited evidence on how the region is prepared for, impacted by and responded to the pandemic.
To examine magnitude of the impact of the COVID-19 pandemic on inequalities in premature mortality in England by deprivation and ethnicity.
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.
Tuberculosis (TB) continues to be a major public health challenge in China. Understanding TB management delays within the context of China’s unique ethnic diversity may be of value in tackling the disease. This study sought to evaluate the impact of ethnic minority status on TB diagnosis and treatment delays.
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.
Honorary Research Associate
Globally, China has the third highest number of tuberculosis (TB) cases despite high rates (85.6%) of effective treatment coverage. Identifying risk factors associated with unsuccessful treatment outcomes is an important component of maximising the efficacy of TB control programmes.
Since 2010, Tanzania has been experiencing frequent outbreaks of dengue. The objectives of this study were to carry out a socio-ecological systems analysis to identify risk factors and interventions and assess the readiness of the district in the prevention and control of dengue.