Estimates of COVID-19 deaths in Mainland China after abandoning zero COVID policy

Abstract

Background: China witnessed a surge of Omicron infections after abandoning zero COVID strategies on December 7, 2022. The authorities report very sparse deaths based on very restricted criteria, but massive deaths are speculated. Methods: We aimed to estimate the COVID-19 fatalities in Mainland China until summer 2023 using the experiences of Hong Kong and of South Korea in 2022 as prototypes. Both these locations experienced massive Omicron waves after having had very few SARS-CoV-2 infections during 2020-2021. We estimated age-stratified infection fatality rates (IFRs) in Hong Kong and South Korea during 2022 and extrapolated to the population age structure of Mainland China. We also accounted separately for deaths of residents in long-term care facilities, which were prominent in Hong Kong. Results: IFR estimates in non-elderly strata were modestly higher in Hong Kong than South Korea and projected 987,455 and 811,571 maximal COVID-19 deaths, respectively, if the entire China population was infected. Expected COVID-19 deaths in Mainland China until summer 2023 ranged from 64,573 to 691,219 assuming 25-70% of the non-elderly population being infected and variable protection of elderly (from none to three-quarter reduction in fatalities). The main analysis (45% of non-elderly population infected and fatality impact among elderly reduced by half) estimated 199,223-249,094 COVID-19 deaths until summer 2023. Large uncertainties exist regarding potential changes in dominant variant, health system strain, and impact on non-COVID-19 deaths. Conclusions: The most critical factor that can affect total COVID-19 fatalities in China is the extent to which the elderly can be protected.

Flaws and uncertainties in pandemic global excess death calculations

“…Reported COVID-19 deaths can be weaponized to prove success or failure of pandemic response measures. In some cases, different stakeholders may endorse extremely different estimates of COVID-19 deaths 9,59 and different interpretations of what happened during the crisis. It is essential to safeguard information on key vital statistics from political, media and other non-scientific interference.…”

“…Other factors, besides demographics, may help capture better the changing nature of populations over time. Adjustment for indicators of frailty, for example, residence in long-term care facilities (LTCFs), may have substantial impact on expected deaths 9 and thus also excess death estimates. Such indicators are ignored in excess death calculations to-date.…”

“…of relevant data varies countries and extrapolations require great caution. For most countries, including the two most populous (India and China 9,59 ), residual uncertainty is likely to be large.…”

“…In these three countries, probably most people were infected before any vaccination, thus age-stratified infection fatality rates for pre-vaccination era 50,51 may apply to most people (IFR may be lower for those vaccinated before being infected). For China, see reference 9 for plausible estimates of COVID-19 deaths during the massive Omicron wave following removal of zero COVID policy measures All mortality estimates in these four countries carry large uncertainty.…”

Inferring China’s excess mortality during the COVID-19 pandemic using online mourning and funeral search volume

“…Prior to China’s departure from Zero-COVID, researchers were concerned about the potential risk associated with such a departure and forecasted likely casualty scenarios. Medical forecasting models usually impose hypothetical values on key parameters 27 , 28 . For example, a calibrated model 27 based on the 2022 Omicron outbreak in Shanghai to project COVID-19 outcome in the absence of non-pharmaceutical interventions suggests about 1.6 million deaths (1.10 deaths per 1000 inhabitants) over a 6-month period.…”