Excess mortality associated with the COVID-19 pandemic during the 2020 and 2021 waves in Antananarivo, Madagascar

Abstract

IntroductionCOVID-19-associated mortality remains difficult to estimate in sub-Saharan Africa because of the lack of comprehensive systems of death registration. Based on death registers referring to the capital city of Madagascar, we sought to estimate the excess mortality during the COVID-19 pandemic and calculate the loss of life expectancy.MethodsDeath records between 2016 and 2021 were used to estimate weekly excess mortality during the pandemic period. To infer its synchrony with circulation of SARS-CoV-2, a cross-wavelet analysis was performed. Life expectancy loss due to the COVID-19 pandemic was calculated by projecting mortality rates using the Lee and Carter model and extrapolating the prepandemic trends (1990–2019). Differences in life expectancy at birth were disaggregated by cause of death.ResultsPeaks of excess mortality in 2020–21 were associated with waves of COVID-19. Estimates of all-cause excess mortality were 38.5 and 64.9 per 100 000 inhabitants in 2020 and 2021, respectively, with excess mortality reaching ≥50% over 6 weeks. In 2021, we quantified a drop of 0.8 and 1.0 years in the life expectancy for men and women, respectively attributable to increased risks of death beyond the age of 60 years.ConclusionWe observed high excess mortality during the pandemic period, in particular around the peaks of SARS-CoV-2 circulation in Antananarivo. Our study highlights the need to implement death registration systems in low-income countries to document true toll of a pandemic.

Excess mortality during the COVID-19 pandemic in low-and lower-middle-income countries: a systematic review and meta-analysis

“…Concerning the source of data, four studies used more than one data source to estimate excess mortality. This included burials in public cemeteries + civil death registration + health authority death registration (Indonesia), daily mortality/incidence data from the Syrian Ministry of Health + Excess all-cause mortality data from a statement by the Damascus governorate + obituary notification data from Facebook page (Syria), National survey data + health facility deaths Jha et al [ 49 ] (India) and figures published by regional governments and Indian journalists + government hospital data + funeral counts + handwritten death registers (India).…”

“…This review identified only one study that assessed factors associated with excess mortality. According to that study, excess deaths were concentrated in urban areas during the first wave of the pandemic but affected both urban and rural areas in the second wave [ 49 ].…”

The Re-Emergence of Rift Valley Fever in Mananjary District, Madagascar in 2021: A Call for Action

“…In Uganda, during the COVID-19 pandemic in 2021, delays in accessing healthcare centers for patients with RVF were reported [ 24 ]. In Madagascar, a delay may be attributed to the concurrent occurrence of the RVF outbreak and the COVID-19 wave observed during the first months of 2021 [ 25 , 26 ]. The various non-pharmaceutical measures implemented during the COVID-19 outbreak made travel between or within regions very difficult.…”

Excess mortality in low-and lower-middle-income countries: A systematic review and meta-analysis

“…All other studies relied on only one data source. Five studies used National Civil Registration Data (Safavi-Naini et al, 33 ; Tadbiri et al 43 ; Ghafari et al, 44 ; Ghafari et al, 46 ; Lewnard et al, 22 ). Two studies each used the Health and Demographic Surveillance System (Otiende et al 35 ; Hani et al, 40 ), death registers (Acosta et al 32 ; Rasambainarivo et al 47 ) and imaging of burial sites/grounds (Besson et al 25 ; Warsame et al 26 ).…”

“…Twelve studies used modelling techniques to estimate excess mortality. Of these, ve studies used linear regression (Lewnard et al; 2021; Wijaya et al, 34 ; Le er et al 31 ; Tadbiri et al 43 ; Ghafari et al, 44 ), two studies used auto-regression modelling techniques (Rasambainarivo et al 47 ; Safavi-Naini et al, 33 ). Two other studies used geospatial analysis which involves identifying new grave plots and measuring changes in burial surface area over a period (Besson et al,25 ; Warsame et al 26 ) and two studies used estimation of death counts (Hedstrom et al, 39 ; Elyazar et al 48 ).…”