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Bearing the brunt of covid-19: older people in low and middle income countries

BMJ 2020; 368 doi: (Published 13 March 2020) Cite this as: BMJ 2020;368:m1052

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Re: Bearing the brunt of covid-19: older people in low and middle income countries

Dear Editor

The article by Lloyd-Sherlock et al. notes that the majority of deaths from the coronavirus pandemic will occur among older people in low and middle-income countries. To help policymakers assess the scale of the challenge to which they must respond, we have created an interactive online tool that estimates the potential number of deaths from COVID-19 in a population, by age group, in individual countries and regional groupings worldwide under a range of scenarios: the Potential Impact of COVID-19 on Human Mortality (PICHM) Tool [1]: This tool applies observed case fatality rates in China or Italy to each population, varying the share of the population that becomes infected.

The core data on COVID-19 confirmed cases, deaths, and case fatality rates by age are taken from publications on China, [2,3] and Italy [4]. The estimates of expected number of deaths in each geographical unit are based on the assumption that case fatality rates by age observed in China or Italy (selected by the user) will apply elsewhere. We estimate the number of expected deaths by age using population estimates from the World Population Prospects, 2019 Revision [5]. Users can select from a wide range of potential infection rates[6], from 1% to 80%, and compute the expected number of deaths by age multiplying three parameters: the population size at each age, the level of infection, and the case fatality rate at age.

The interactive PICHM Tool includes a table showing the population distribution, estimated case fatality rates, and expected number of deaths by ages for fixed scenarios where 50%, 25% and 10% of the population become infected by COVID-19. A bar chart shows the population size, case fatality rates, and estimated number of deaths by age for the level of infection selected by the user. The PICHM tool allows users to select the geographical unit and estimate parameters under different scenarios.

The tool allows user to interact with a large volume of data via a simple, easy-to-use user interface. Using the location selector, the user can explore estimates of the expected number of deaths by age for the World, multiple regions of the World, groups of regions, and countries and territories. For example, in Nigeria with a 25% infection rate scenario it estimates a total of 229,399 deaths of which 124,123 will be among people aged 60 and over.

Results should be interpreted with caution given several assumptions. The method used to estimate the expected number of deaths assumes that 1) the case fatality rate due COVID-19 by age in a specific location is like that observed in China or Italy; 2) the distribution of case fatality by age remains constant everywhere; 3) the infection rate is the same at every age; and 4) the quantified CFR in China or Italy is actually the underlying CFR. These assumptions are unlikely to be robust, but are the best currently available when developing estimates. They will be revised as more information becomes available.

The tool has the widest coverage among tools for predicting COVID-19 mortality on the basis of current knowledge. It will be of particular value in low and middle-income countries, where analytic capacity may be limited. The interpretation of the results and their communication should be careful and responsible as the purpose of this tool is to inform, not to scaremonger.


1. Ramon Martinez, Eng, Shah Ebrahim, Lucas Sempe and Martin McKee. Potential impact of COVID-19 on human mortality tool
2. The Novel Coronavirus Pneumonia Emergency Response Epidemiology Team. Vital Surveillance: The Epidemiological Characteristics of an Outbreak of 2019 Novel Coronavirus Diseases (COVID-19) — China, 2020. China CDC Weekly, 2020;2(8):113-122. (accessed 14 March 2020)
3. Report of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID-19) [Pdf] - World Health Organization, Feb. 28, 2020. (accessed 14 March 2020)
4. Epidemia COVID-19. Aggiornamento nazionale 12 marzo 2020. Istituto Superiore di Sanità, Roma. (accessed 15 march 2020)
5.- UN. World Population Prospects, 2019 Revision. Population Division, Department of Economics and Social Affairs, United Nations. 2019.
6. UK Government. Scientific Pandemic Influenza Modelling. 2018

Competing interests: No competing interests

18 March 2020
Peter G Lloyd-Sherlock
Ramon Martinez, Eng, Shah Ebrahim, Lucas Sempe and Martin McKee.
University of East Anglia
University of East Anglia, Norwich, UK