Grant: Operating Grant: COVID-19 - Clinical management

The current global infectious threat, COVID-19, has not yet been widely detected in sub-Saharan Africa or other low income countries in Asia. It is almost inevitable that it will reach those places. While unusual spikes in infection-related deaths can register quickly in higher income countries and in China, they can go unrecognized for weeks or months in low-income settings where even very ill people do not go to a hospital, infecting others. Detecting a mortality signal is important and may be the first step in recognizing a serious outbreak. We propose to build on our extensive experience using verbal autopsy (VA) in the long-running Indian Million Death Study, and ongoing studies in China, Hong Kong, Ethiopia and Sierra Leone to develop an enhanced verbal autopsy module to identify deaths from COVID-19. This will serve as a model for the next novel pathogen-as near as possible to real time in settings without routine medical certification of death. We will test three hypotheses: #1 An "Acute Respiratory Mortality Surveillance" (ARMS) module can be added quickly to the WHO VA instrument and validated against hospitalized cases and deaths (paired with epidemiological information and machine learning) to distinguish COVID-19 from other causes of respiratory deaths. #2 Early deployment of ARMS in China, Hong Kong, India, Sierra Leone, and Ethiopia will help establish baseline distributions of usual acute respiratory deaths, as a comparator for COVID-19 deaths, and to inform modelling. #3 Effective knowledge translation of an open-source, widely-available ARMS module will improve the global response to COVID-19, particularly in the lowest income countries and help to improve mortality assessments for any subsequent COVID-19 waves. A successful ARMS will contribute to stopping the current outbreak and add novel surveillance tools. All materials and results will be made available globally to ensure the broadest use.