Tying rapid response to smart testing: Empowering local government response in Pakistan’s COVID-19 outbreak

In the wake of the COVID-19 pandemic, governments across the world have been grappling with how to determine the prevalence of the virus in their own countries and introduce policy responses that will best mitigate its impact. No ‘optimal’ testing strategy has emerged and a shortage of tests has limited the information on population prevalence and transmission rates; some countries chose to go into lockdown halting their economic activities and consequently worsening socio-economic outcomes. Meanwhile, evidence suggests that lockdowns are not a panacea for the outbreak, rather giving governments time to prepare a more effective response. However, lockdowns impose very heavy costs for low-income countries like Pakistan.

This project examines how the Pakistani government can deliver an evidence-driven rapid policy response at the right level to maximise lives saved and minimise economic costs, containing the viral spread through systematic and data-driven measures that help governments learn faster. By determining the extent of the remedial social distancing measures through an iterative process based on existing and future prevalence rates, we can better mitigate socio-economic costs and enhance the effectiveness of these remedial measures. In doing so, we can build the capacity for governments to respond in a timely and more systematic way to the crises to ensure they do not adversely affect current and future growth. 

This project leverages a unique partnership with provincial governments in Pakistan to explore this question in two steps:

  1. Developing and piloting systematic smart testing to collect real-time data on virus prevalence, transmission and correlating factors, thereby decreasing uncertainty about transmission patterns and;
  2. Providing evidence-based real-time feedback to government counterparts on localized (district-level) situations and the effectiveness of policy responses.

Outputs

  • Research in progress.

    Project last updated on: 23 Apr 2021.