HIT-COVID, a global database tracking public health interventions to COVID-19

Abstract

The COVID-19 pandemic has sparked unprecedented public health and social measures (PHSM) by national and local governments, including border restrictions, school closures, mandatory facemask use and stay at home orders. Quantifying the effectiveness of these interventions in reducing disease transmission is key to rational policy making in response to the current and future pandemics. In order to estimate the effectiveness of these interventions, detailed descriptions of their timelines, scale and scope are needed. The Health Intervention Tracking for COVID-19 (HIT-COVID) is a curated and standardized global database that catalogues the implementation and relaxation of COVID-19 related PHSM. With a team of over 200 volunteer contributors, we assembled policy timelines for a range of key PHSM aimed at reducing COVID-19 risk for the national and first administrative levels (e.g. provinces and states) globally, including details such as the degree of implementation and targeted populations. We continue to maintain and adapt this database to the changing COVID-19 landscape so it can serve as a resource for researchers and policymakers alike.

Mask-wearing and control of SARS-CoV-2 transmission in the USA: a cross-sectional study

“…A state that has high rates of physical distancing might also be subject to additional non-modelled interventions that still have a strong effect, including gathering size reductions, travel limitations, and the closing of businesses. 27 Although the physical distancing proxy used here captures the broad activity of individuals that would result from the implementation of these policies, future research should focus on incorporating data from disaggregated interventions with empirical assessments of mask-wearing. However, these measures and our methods do not account for other public health interventions, such as contact tracing and diagnostic testing, which might play a large role in transmission control.…”

A structured open dataset of government interventions in response to COVID-19

“…During the COVID-19 crisis, other projects have concomitantly tracked data on government policies (interchangeably named NPIs 18 or government(s') responses 26,28,29 or government measures 30 or PHSM 31 or policy actions 26 ). We report here on five of them 26,[28][29][30][31] in order to contextualise our work.…”

“…During the COVID-19 crisis, other projects have concomitantly tracked data on government policies (interchangeably named NPIs 18 or government(s') responses 26,28,29 or government measures 30 or PHSM 31 or policy actions 26 ). We report here on five of them 26,[28][29][30][31] in order to contextualise our work. The comparison indicates similarities and differences among the NPI trackers and highlights how the CCCSL Country-cluster analysis based on the number of mandatory government interventions and respective dates of implementation, as calculated using the epidemic age (t 0 = day when 10 cases were reported) (http:// covid19-interventions.com/CountryClusters.html).…”

What Is the Impact of Lockdowns on Dengue?

“…Lockdowns indeed showed great success in containing the COVID-19 outbreak in the initial epicentre in Wuhan, China [ 2 ] and flattened the curve in many other countries [ 3 ]. Each country has taken different approaches to lockdowns with the restrictiveness, adherence, target population and duration of lockdowns varying considerably between countries [ 4 ]. The unprecedented lockdowns, despite their major repercussions on the economy and mental health [ 5 ], also led to the decline of other diseases that are transmitted from human to human.…”