Coronavirus pandemic in the South Asia region: Health policy and economy trade-off

Furqan B Irfan; Ben Telford; Nick Hollon; Ali Dehghani; Casey Schukow; Ayesha Yasmeen Syed; Ryan T Rego; Akbar K Waljee; William Cunningham; Fahad Shabbir Ahmed

doi:10.7189/jogh.13.06014

Coronavirus pandemic in the South Asia region: Health policy and economy trade-off

J Glob Health. 2023 May 5:13:06014. doi: 10.7189/jogh.13.06014.

Authors

Furqan B Irfan^{1

2}, Ben Telford³, Nick Hollon³, Ali Dehghani³, Casey Schukow³, Ayesha Yasmeen Syed⁴, Ryan T Rego⁵, Akbar K Waljee^{5

6

7}, William Cunningham¹, Fahad Shabbir Ahmed⁸

Affiliations

¹ Institute of Global Health, Michigan State University, East Lansing, Michigan, USA.
² Department of Neurology and Ophthalmology, College of Osteopathic Medicine, Michigan State University, East Lansing, Michigan, USA.
³ College of Osteopathic Medicine, Michigan State University, East Lansing, Michigan, USA.
⁴ Wayne Medical Center, Westland, Michigan, USA.
⁵ Center for Global Health Equity, University of Michigan, Ann Arbor, Michigan, USA.
⁶ Department of Learning Health Sciences, University of Michigan, Ann Arbor, Michigan, USA.
⁷ Michigan Integrated Center for Health Analytics and Medical Prediction (MiCHAMP), University of Michigan, Ann Arbor, Michigan, USA.
⁸ Department of Pathology, Wayne State University, Detroit, Michigan, USA.

Abstract

Background: The South Asian Association for Regional Cooperation (SAARC) covers Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka. We conducted a comparative analysis of the trade-off between the health policies for the prevention of COVID-19 spread and the impact of these policies on the economies and livelihoods of the South Asia populations.

Methods: We analyzed COVID-19 data on epidemiology, public health and health policy, health system capacity, and macroeconomic indicators from January 2020 to March 2021 to determine temporal trends by conducting joinpoint regression analysis using average weekly percent change (AWPC).

Results: Bangladesh had the highest statistically significant AWPC for new COVID-19 cases (17.0; 95% CI = 7.7-27.1, P < 0.001), followed by the Maldives (12.9; 95% CI = 5.3-21.0, P < 0.001) and India (10.0; 95% CI = 8.4-11.5, P < 0.001). The AWPC for COVID-19 deaths was significant for India (6.5; 95% CI = 4.3-8.9, P < 0.001) and Bangladesh (6.1; 95% CI = 3.7-8.5, P < 0.001). Nepal (55.79%), and India (34.91%) had the second- and third-highest increase in unemployment, while Afghanistan (6.83%) and Pakistan (16.83%) had the lowest. The rate of change of real GDP had the highest decrease for Maldives (557.51%), and India (297.03%); Pakistan (46.46%) and Bangladesh (70.80%), however, had the lowest decrease. The government response stringency index for Pakistan had a see-saw pattern with a sharp decline followed by an increase in the government health policy restrictions that approximated the test-positivity trend.

Conclusions: Unlike developed economies, the South Asian developing countries experienced a trade-off between health policy and their economies during the COVID-19 pandemic. South Asian countries (Nepal and India), with extended periods of lockdowns and a mismatch between temporal trends of government response stringency index and the test-positivity or disease incidence, had higher adverse economic effects, unemployment, and burden of COVID-19. Pakistan demonstrated targeted lockdowns with a rapid see-saw pattern of government health policy response that approximated the test-positivity trend and resulted in lesser adverse economic effects, unemployment, and burden of COVID-19.

MeSH terms

Asia, Southern
Bangladesh / epidemiology
COVID-19*
Communicable Disease Control
Health Policy
Humans
India / epidemiology
Pakistan / epidemiology
Pandemics*