Long-term trends in seasonality of mortality in urban Madagascar: the role of the epidemiological transition

Abstract

Background: Seasonal patterns of mortality have been identified in Sub-Saharan Africa but their changes over time are not well documented. Objective: Based on death notification data from Antananarivo, the capital city of Madagascar, this study assesses seasonal patterns of all-cause and cause-specific mortality by age groups and evaluates how these patterns changed over the period 1976-2015. Methods: Monthly numbers of deaths by cause were obtained from death registers maintained by the Municipal Hygiene Office in charge of verifying deaths before the issuance of burial permits. Generalized Additive Mixed regression models (GAMM) were used to test for seasonality in mortality and its changes over the last four decades, controlling for long-term trends in mortality. Results: Among children, risks of dying were the highest during the hot and rainy season, but seasonality in child mortality has significantly declined since the mid-1970s, as a result of declines in the burden of infectious diseases and nutritional deficiencies. In adults aged 60 and above, all-cause mortality rates are the highest in the dry and cold season, due to peaks in cardiovascular diseases, with little change over time. Overall, changes in the seasonality of all-cause mortality have been driven by shifts in the hierarchy of causes of death, while changes in the seasonality within broad categories of causes of death have been modest. Conclusion: Shifts in disease patterns brought about by the epidemiological transition, rather than changes in seasonal variation in cause-specific mortality, are the main drivers of trends in the seasonality of all-cause mortality. ARTICLE HISTORY

Evidências da Polarização Epidemiológica no Nordeste Brasileiro: Análise Espacial Pelas Técnicas de Regionalização e de Aglomerados de Áreas

“…Os resultados do presente estudo revelam um perfil hegemônico de acometimento por doenças e agravos não transmissíveis, tendência em todo o mundo (CALAZANS; QUEIROZ, 2020;JAGANNATHAN et al, 2019;SCHLÜTERA et al, 2020). Diante desse cenário, a ascensão das doenças e agravos crônico-degenerativos se dá por intermédio de mudanças nas dinâmicas sociais, tais como envelhecimento populacional, número médio de anos vividos na idade adulta, além de condições socioeconômicas e estilo de vida (CALAZANS; QUEIROZ, 2020).…”

Seasonal variation in infant mortality in India

“…More contemporary studies on seasonality and health have contributed to the scientific understanding of health determinants, dynamics, and public policy. These studies have documented reductions in seasonal variation along the epidemiological transition in both historical and contemporary contexts (Delaunay et al, 2001;Rau, 2006b;Schl üter et al, 2020). They have also shed light on understand vulnerability to climactic factors (Rayco-Solon et al, 2004;Muhuri, 1996); identified the importance of household technologies, such as those related to temperature control (Kunst et al, 1991); motivated social security interventions in lean seasons (Behrman, 1988b;Drèze, 1990;Kumar et al, 2016); and quantified the likely impact of health interventions targeting seasonal diseases, such as malaria (Etard et al, 2004), influenza (Dorélien, 2019;Ho and Noymer, 2017), and diarrhea (Farrar et al, 2019).…”

Monitoring for outbreak-associated excess mortality in an African city: Detection limits in Antananarivo, Madagascar

“…While death registration systems are often deficient at the national level, some urban centers maintain complete and up-todate registers. In Antananarivo, the capital city of Madagascar, detailed mortality data maintained since 1976 have provided a unique window onto questions ranging from the drivers of the epidemiological transition in low income settings to changes in seasonality in mortality across four decades (Masquelier et al, 2019;Schlüter et al, 2020). These unique data open the way to detecting disease driven-anomalies in mortality data in a lower income setting as was shown during the 2009 Influenza (AH1N1) virus pandemic (Rajatonirina et al, 2013).…”

“…However, the higher incidence of infectious diseases in such settings also drives strong background fluctuations in mortality (seasonal and often age specific) that must be accounted for, and might impede detection of mortality anomalies. For instance, Schlüter (Schlüter et al, 2020) et al showed that in Antananarivo, deaths in adults >65 years old peak during the austral winter months (June-September) while that of children peak in December -January. Therefore, an unexpected increase in mortality of elder individuals, concurrent with the decrease in mortalities of children or vice-versa may be inapparent or appear to be of a lesser extent when considering the entire population.…”