Risk of death by age and gender from CoVID-19 in Peru, March-May, 2020

Abstract

Peru implemented strict social distancing measures during the early phase of the epidemic and is now experiencing one of the largest CoVID-19 epidemics in Latin America. Estimates of disease severity are an essential indicator to inform policy decisions about the intensity and duration of interventions needed to mitigate the outbreak. Here we derive delay-adjusted case fatality risks (aCFR) of CoVID-19 in a middle-income country in South America.We utilize government-reported time series of CoVID-19 cases and deaths in Peru stratified by age group and gender.As of May 25, 2020, we estimate the aCFR for men and women at 10.8% (95%CrI: 10.5-11.1%) and 6.5% (95%CrI: 6.2-6.8%), respectively, whereas the overall aCFR was estimated at 9.1% (95%CrI: 8.9-9.3%). Our results show that senior individuals have been the most severely affected by CoVID-19, particularly men, with an aCFR of nearly 60% for those aged 80- years. We also found that men have a significantly higher cumulative morbidity ratio across most age groups (proportion test, p-value< 0.001), with the exception of those aged 0-9 years.The ongoing CoVID-19 pandemic is generating a substantial mortality burden in Peru. Senior individuals, especially those older than 70 years, are being disproportionately affected by the CoVID-19 pandemic.

Keywords: 2020; COVID-19; Peru; risk of death; time-delay adjusted CFR.

Figure 1

Epidemiological characterization of CoVID-19 in Peru, as of May 25, 2020. (A) Age distribution of reported cases by gender, (B) Age distribution of reported deaths by gender. (C) Gender proportion of CoVID-19 cases by age group, (D) Gender proportion of CoVID-19 deaths by age group, (E) Cumulative morbidity risk by gender and age group, (F) Mortality directly caused by CoVID-19 by gender and age group.

Figure 2

Temporal distribution of cases and deaths by age group due to CoVID-19, March-May 2020, Peru. Top: Male, cumulative cases, Second top: Male, cumulative cases, Second bottom: Female, cumulative cases, Bottom: Female cumulative deaths (A) aged 0-9, (B) aged 10-19, (C) aged 20-29, (D) aged 30-39, (E) aged 40-49, (F) aged 50-59, (G) aged 60-69, (H) aged 70-79, (I) aged 80- and (J) Overall (all age groups). Day 1 corresponds to March 1^st in 2020.

Figure 3

Temporal variation of male and female risk of death by age group caused by CoVID-19, March-May 2020, Peru. Upper two rows; Male risk of deaths, Lower two rows; Female risk of deaths. Observed and posterior estimated of crude case fatality risk of (A) aged 0-9, (B) aged 10-19, (C) aged 20-29, (D) aged 30-39, (E) aged 40-49, (F) aged 50-59, (G) aged 60-69, (H) aged 70-79, (I) aged 80-, (J) all age groups and time-delay adjusted case fatality risk of (K) aged 0-9, (L) aged 10-19, (M) aged 20-29, (N) aged 30-39, (O) aged 40-49, (P) aged 50-59, (Q) aged 60-69, (R) aged 70-79, (S) aged 80-, (T) all age groups. Day 1 corresponds to March 1^st in 2020. Black dots show crude case fatality risk, and light and dark indicates 95% and 50% credible intervals for posterior estimates, respectively.

Figure 4

Most recent estimates of time-delay adjusted risk of death caused by CoVID-19 by age group and gender, March-May 2020, Peru. Distribution of time-delay adjusted risk of death from the latest estimates (May 25, 2020) is presented. Top to bottom: female aged 0-9, female aged 10-19, female aged 20-29, female aged 30-39, female aged 40-49, female aged 50-59, female aged 60-69, female aged 70-79, female aged 80 and over, female overall.