The current pandemic due to Coronavirus Disease 2019 (COVID-19) has led to the unprecedented use of non pharmaceutical interventions (NPI), including limiting travel, closing business and schools, and ordering people to shelter in place. While these extreme interventions are effective in slowing transmission of the disease, it is not clear how they can best be implemented and how other local factors (such as population density, age structure, timing in the outbreak, and smoking prevalence) might impact their efficacy. We are building a global database of these interventions in order to more carefully explore these questions and allow other researchers to use this data in their research. We will create models to better understand how NPI impact disease transmission and how the local context effects the impact of these NPI. We are working with colleagues in NYC, Spain, and Italy with more granular data to better explore these problems.
We aim to develop a framework that is applicable to widely available case notification data. As the disease spreads to vulnerable populations, such as people experiencing homelessness, persons living with HIV (PLWH) and TB, we anticipate that the impact on these populations will be more severe and with a higher force of infection. We will are involved in an effort to build a COVID-19 patient data warehouse at Boston Medical Center, the largest safety net hospital in New England. This will also include COVID-19 treatment and testing data from Boston Healthcare for the Homeless. We will use this data to study the impact of COVID-19 on these vulnerable populations. We will also leverage our strong relationships with collaborators in South Africa, the Philippines, and Ukraine, where the prevalence of these conditions is much higher, in order to better elucidate transmission patterns and impact in the developing world. We will estimate the impact of potential treatment disruptions due to the pandemic response on HIV and TB populations.
The current COVID-19 pandemic is leading to the unprecedented use of non pharmaceutical interventions to limit its spread, bringing significant economic and mental health consequences. We are tracking these interventions, and modeling their efficacy accounting for the local context in which they are implemented. We are also working to track and study the impact of COVID-19 on vulnerable populations, such as persons living with HIV and TB, persons experiencing homelessness, and substance users.
| McIntosh, Avery I; Jenkins, Helen E; White, Laura F et al. (2018) Using routinely collected laboratory data to identify high rifampicin-resistant tuberculosis burden communities in the Western Cape Province, South Africa: A retrospective spatiotemporal analysis. PLoS Med 15:e1002638 |
| Ma, Y; Horsburgh, C R; White, L F et al. (2018) Quantifying TB transmission: a systematic review of reproduction number and serial interval estimates for tuberculosis. Epidemiol Infect 146:1478-1494 |
