A proposed analytical approach to estimate excess daily mortality rates in Ecuador.

Background: The COVID-19 pandemic has proved deadly all over the globe; however, one of the most lethal outbreaks occurred in Ecuador. Aims: This study aims to highlight the pandemic's impact on the most affected countries worldwide in terms of excess deaths per capita and per day. Methods: An ecological study of all-cause mortality recorded in Ecuador was performed. To calculate the excess deaths relative to the historical average for the same dates in 2017, 2018, and 2019, we developed a bootstrap method based on the central tendency measure of mean. A Poisson fitting analysis was used to identify trends on officially recorded all-cause deaths and COVID-19 deaths. A bootstrapping technique was used to emulate the sampling distribution of our expected deaths estimator µâŒ¢deaths by simulating the data generation and model fitting processes daily since the first confirmed case. Results: In Ecuador, during 2020, 115,070 deaths were reported and 42,453 were cataloged as excess mortality when compared to 2017-2019 period. Ecuador is the country with the highest recorded excess mortality in the world within the shortest timespan. In one single day, Ecuador recorded 1,120 deaths (6/100,000), which represents an additional 408% of the expected fatalities. Conclusion: Adjusting for population size and time, the hardest-hit country due to the COVID-19 pandemic was Ecuador. The mortality excess rate shows that the SARS-CoV-2 virus spread rapidly in Ecuador, especially in the coastal region. Our results and the proposed new methodology could help to address the real situation of the number of deaths during the initial phase of pandemics.

COVID-19 Excess Deaths in Peru's 25 States in 2020: Nationwide Trends, Confounding Factors, and Correlations With the Extent of Ivermectin Treatment by State.

Introduction In 2020, nations hastened to contain an emerging COVID-19 pandemic by deploying diverse public health approaches, but conclusive appraisals of the efficacy of these approaches are elusive in most cases. One of the medicines deployed, ivermectin (IVM), a macrocyclic lactone having biochemical activity against SARS-CoV-2 through competitive binding to its spike protein, has yielded mixed results in randomized clinical trials (RCTs) for COVID-19 treatments. In Peru, an opportunity to track the efficacy of IVM with a close consideration of confounding factors was provided through data for excess deaths as correlated with IVM use in 2020, under semi-autonomous policies in its 25 states. Methods To evaluate possible IVM treatment effects, excess deaths as determined from Peruvian national health data were analyzed by state for ages ≥60 in Peru's 25 states. These data were compared with monthly summary data for excess deaths in Peru for the period 2020-2021 as published by the WHO in 2022. To identify potential confounding factors, Google mobility data, population densities, SARS-CoV-2 genetic variations, and seropositivity rates were also examined. Results Reductions in excess deaths over a period of 30 days after peak deaths averaged 74% in the 10 states with the most intensive IVM use. As determined across all 25 states, these reductions in excess deaths correlated closely with the extent of IVM use (p<0.002). During four months of IVM use in 2020, before a new president of Peru restricted its use, there was a 14-fold reduction in nationwide excess deaths and then a 13-fold increase in the two months following the restriction of IVM use. Notably, these trends in nationwide excess deaths align with WHO summary data for the same period in Peru. Conclusions The natural experiment that was put into motion with the authorization of IVM use for COVID-19 in Peru in May 2020, as analyzed using data on excess deaths by locality and by state from Peruvian national health sources, resulted in strong evidence for the drug's effectiveness. Several potential confounding factors, including effects of a social isolation mandate imposed in May 2020, variations in the genetic makeup of the SARS-CoV-2 virus, and differences in seropositivity rates and population densities across the 25 states, were considered but did not appear to have significantly influenced these outcomes.

Estimating Excess Mortality Due to Prostate, Breast, and Uterus Cancer during the COVID-19 Pandemic in Peru: A Time Series Analysis.

During the COVID-19 pandemic, most of the deaths in Peru were related to COVID-19; however, cancer deaths have also been exacerbated in the first months of the pandemic. Despite this, excess mortalities of prostate, breast, and uterus cancer are not available by age group and region from January to December 2020. Therefore, we estimated the excess deaths and excess death rates (per 100,000 habitants) due to prostate, breast, and uterus cancer in 25 Peruvian regions. We did a time series analysis. Prostate, breast, and uterus cancer death data for 25 Peruvian regions were retrieved during the COVID-19 pandemic in 2020, as well as data for up to 3 years prior (2017-2019) from the Sistema Informatico Nacional de Defunciones at the Ministry of Health of Peru. Deaths in 2020 were defined as observed deaths. The expected deaths (in 2020) were estimated using the average deaths over 3 preceding years (2017, 2018 and 2019). Excess mortality was calculated as the difference between observed mortality and expected mortality in 2020. We estimated that the number of excess deaths and the excess death rates due to prostate, breast, and uterus cancer were 610 deaths (55%; 12.8 deaths per 100,000 men), 443 deaths (43%; 6 deaths per 100,000 women), and 154 deaths (25%; 2 deaths per 100,000 women), respectively. Excess numbers of deaths and excess death rates due to prostate and breast cancer increased with age. These excess deaths were higher in men aged ≥ 80 years (596 deaths (64%) and 150 deaths per 100,000 men) and women aged 70-79 years (229 deaths (58%) and 15 deaths per 100,000 women), respectively. In summary, during the COVID-19 pandemic, there were excess prostate and breast cancer mortalities in 2020 in Peru, while excess uterus cancer mortalities were low. Age-stratified excess death rates for prostate cancer and breast cancer were higher in men ≥ 80 years and in women ≥ 70 years, respectively.

Excess mortality from COVID 19 in Costa Rica: a registry based study using Poisson regression.

Background: Official death toll related to COVID-19 has been considerably underestimated in reports from some Latin American countries. This study aimed to analyze the mortality associated with the COVID-19 pandemic in Costa Rica between March 2020 and December 2021. Methods: A registry based study based on 2017-2021 data from the National Institute of Statistics and Census was designed (N = 128,106). Excess deaths were defined by the WHO as "the difference in the total number of deaths in a crisis compared to those expected under normal conditions"; and were estimated using a Poisson regression, and mortality and years of potential life lost (YPLL) rates were calculated. Findings: The COVID-19 pandemic represented 15% of the deaths in Costa Rica between March 2020 and December 2021. The mortality rate related to COVID-19 was 83 per 100,000 person-years. Between March and July 2020 (low-incidence period), observed number of deaths was 9%-lower than expected, whereas it was 15% and 24% higher than expected between July 2020 and March 2021 (high incidence period - no vaccination), and between March 2021 and December 2021 (high incidence period - progressive vaccination) respectively. Between July 2020 and December 2021, excess deaths observed and COVID-19 deaths reported were comparable (7461 and 7620 respectively). Nevertheless, there were more deaths than expected for conditions that predispose to COVID-19 deaths. YPLL and mortality rates increased with age, but significant excess deaths were observed in all age-groups older than 30-39 years. No large differences were noted by districts' socioeconomic characteristics although excess death rate was lower in rural compared to urban areas. Interpretation: Reporting of deaths was only slightly underestimated. In the pre-vaccination period, mortality rate and YPLL rates increased with age, being highest in people aged 60 years or older and justifying the decision to initially prioritize vaccination of older individuals. Funding: The study was supported by the University of Costa Rica and the Agencia Costarricense de Investigaciones Biomédicas - Fundación Inciensa.

Más sobre el exceso de muertes por la pandemia de COVID-19

Introducción: En las últimas semanas de 2022 aparecen nuevas informaciones acerca del exceso de muertes durante la pandemia de COVID-19 en 2020 y 2021 en múltiples naciones. Objetivo: Comentar los aspectos de mayor interés en las últimas informaciones publicadas. Métodos: Análisis de documentos sobre COVID-19 publicados en 2020 y 2021 y síntesis de la información recopilada. Resultados: Un importante estudio de la OMS estima un exceso de muertes de 14,83 (13,23 ± 16,58) millones más de las esperadas en todo el mundo, durante 2020 y 2021. Estos estimados son más conservadores que los de otras instituciones que estimaron entre 16 y 18,2 millones. El informe de OMS estima que cuatro de cada cinco países con mayores excesos de muertes ocurren en estados de "medianos ingresos", con algunos de los peores 25 resultados en América Latina (Cuba no está incluida). No se documenta todavía lo ocurrido durante 2022 que ya termina. Conclusiones: En el futuro se debe mantener la vigilancia de la evolución de las cifras de mortalidad y la estructura por causas de muerte en las poblaciones.

Introduction: In the last weeks of 2022, new information appears about the excess deaths during the COVID-19 pandemic in 2020 and 2021 in multiple nations. Objective: To comment on the aspects of greatest interest in those cited documents. Methods: Analysis of documents on COVID-19 was conducted on those published in 2020 and 2021 and synthesis of the information collected. Results: A major WHO study estimates an excess of deaths of 14.83 (13.23 ± 16.58) million more than expected worldwide, during 2020 and 2021. These estimates are more conservative than those of other institutions that estimated between 16 and 18.2 million. The WHO report estimates that four out of five countries with the highest excess deaths occur in "middle-income" states, with some of the worst outcomes in Latin America. Cuba is not included. What happened during 2022, which is already ending, has not yet been documented. Conclusions: It is considered that monitoring of the evolution of mortality figures and the structure by causes of death in populations should be maintained in the future.

Excesso de óbitos classificados com códigos garbage na pandemia de Covid-19, no estado da Paraíba / Excess of deaths classified with garbage codes in the COVID-19 pandemic / Exceso de muertes clasificados con códigos garbage en la pandemia COVID-19

Resumo No cenário de calamidade assistido durante a pandemia de Covid-19, o ato de definir a causa básica de um óbito não foi trivial e o aumento da utilização dos códigos garbage (códigos mal definidos ou pouco específicos) traz preocupação em relação à qualidade da informação sobre as causas de morte nos estados do Brasil. Constatou-se um aumento significativo do número de óbitos no período pandêmico no estado da Paraíba, localizado na região Nordeste do Brasil, situação que se assemelhou ao contexto nacional. Em 2020 ocorreram 31.107 óbitos na Paraíba, enquanto no período de 2015 a 2019 foi identificada uma média de 27.000 óbitos. O objetivo do presente estudo é identificar e mensurar o excesso de óbitos classificados com códigos garbage em 2020, no estado da Paraíba, durante a pandemia de Covid-19. As séries temporais de óbitos foram obtidas do Painel de Monitoramento da Mortalidade por Causas Básicas Inespecíficas ou Incompletas (garbage codes) do Ministério da Saúde, para todos os meses de 2015 a 2020. Foram calculadas as projeções de óbitos totais e dos óbitos por códigos garbage (CG). O cálculo do excesso da proporção de óbitos classificados por códigos garbage no estado da Paraíba, em 2020, resultou em 8,58%, destacando-se o mês de junho com o maior valor (19,42%). Espera-se contribuir para avanços no conhecimento da realidade da qualidade da informação da notificação dos óbitos em uma área do país que almeja avanços nesse sentido e evidenciar a necessidade da investigação em outras localidades do Brasil.

Abstract In the disaster scenario witnessed during the pandemic caused by COVID-19, the act of defining the underlying cause of a death was no trivial matter and the increased use of Garbage Codes (poorly defined or not very specific codes) raises concerns regarding the quality of the information on causes of death in the states of Brazil. There was a significant increase in the number of deaths during the pandemic in the state of Paraíba, located in the Northeast region of Brazil, a situation similar to the national context. There were 31,107 deaths in 2020 in Paraíba, while an average of 27,000 deaths were identified for the period 2015 to 2019. Our goal was to identify and measure the excess of deaths classified with Garbage Codes in the COVID-19 pandemic in the geographic space of the state of Paraíba in 2020. The time series of deaths were obtained from the Mortality Monitoring Panel for Unspecific or Incomplete Basic Causes (Garbage Codes) of the Ministry of Health, for all months of the years 2015 to 2020. Projections of total deaths and deaths by Garbage Codes (GC) were calculated. The calculation of the excess proportion of deaths classified by Garbage Codes in the state of Paraíba resulted in 8.58%, highlighting the month of June 2020, which reached the maximum value equal to 19.42%. We expect to contribute to advance knowledge regarding the current reality of quality information on death notifications in an area of the country that seeks to make progress in this direction and to highlight the need for research in other locations in Brazil.

Resumen En el escenario de desastre que se vivió durante la pandemia de COVID-19, definir la causa subyacente de una muerte no fue baladí y el aumento del uso de códigos garbage (códigos mal definidos o poco específicos) genera preocupaciones acerca la calidad de la información sobre las causas de muerte en los estados de Brasil. En cuanto al aumento del número de muertes en el período de la pandemia en el estado de Paraíba, en la región Nordeste de Brasil, la situación fue similar al contexto nacional: 31.107 muertes en 2020, mientras que durante el período 2015-2019 el promedio fue de 27.000 muertes. El objetivo de este trabajo fue identificar y medir el exceso de muertes clasificadas con códigos Garbage en la pandemia de COVID-19 en el estado de Paraíba en 2020. Las series temporales de defunciones se obtuvieron del Panel de Seguimiento de Mortalidad por Causas Básicas Inespecíficas o Incompletas del Ministerio de Salud, para todos los meses de 2015 a 2020. Se calcularon proyecciones de muertes totales y muertes por códigos basura, para los que el cálculo de la proporción de exceso de muertes resultó en 8,58 %, con un valor de 19,42 % durante junio. Se espera contribuir a la calidad de la información sobre las notificaciones de muerte en un área del país que busca avances en esa dirección y resaltar la necesidad de investigaciones en otras localidades de Brasil.

Disparities in Excess Mortality Between Indigenous and Non-Indigenous Brazilians in 2020: Measuring the Effects of the COVID-19 Pandemic.

This study aimed to estimate the number of excess deaths among Indigenous Peoples associated with the COVID-19 pandemic in 2020 and to assess the disparities in excess mortality between Indigenous and non-Indigenous Brazilians. A time series analysis of weekly mortality data including all deaths from January 2015 to December 2020 was conducted. The number of expected deaths for 2020 was estimated using an over-dispersed Poisson model that accounts for demographic changes, temporal trends, and seasonal effects in mortality. Weekly excess deaths were calculated as the difference between the number of observed deaths and the expected deaths. Regional differences in Indigenous mortality were investigated. A significant increase in Indigenous mortality was observed from April 1 to December 31, 2020. An estimated 1149 (95% CI 1018-1281) excess deaths was found among Indigenous Brazilians in 2020, representing a 34.8% increase from the expected deaths for this population. The overall increase in non-Indigenous mortality was 18.1%. The Indigenous population living in the Brazilian Amazon area was the earliest-affected Indigenous group, with one of the highest proportional increases in mortality. Disparities in excess mortality revealed a disproportionate burden of COVID-19 among Indigenous Brazilians compared to their non-Indigenous counterparts. Findings highlight the importance of implementing an effective emergency plan that addresses the increased vulnerability of Indigenous Peoples to COVID-19.

Excess deaths reveal the true spatial, temporal and demographic impact of COVID-19 on mortality in Ecuador.

BACKGROUND: In early 2020, Ecuador reported one of the highest surges of per capita deaths across the globe. METHODS: We collected a comprehensive dataset containing individual death records between 2015 and 2020, from the Ecuadorian National Institute of Statistics and Census and the Ecuadorian Ministry of Government. We computed the number of excess deaths across time, geographical locations and demographic groups using Poisson regression methods. RESULTS: Between 1 January and 23 September 2020, the number of excess deaths in Ecuador was 36 402 [95% confidence interval (CI): 35 762-36 827] or 208 per 100 000 people, which is 171% of the expected deaths in that period in a typical year. Only 20% of the excess deaths are attributable to confirmed COVID-19 deaths. Strikingly, in provinces that were most affected by COVID-19 such as Guayas and Santa Elena, the all-cause deaths are more than double the expected number of deaths that would have occurred in a normal year. The extent of excess deaths in men is higher than in women, and the number of excess deaths increases with age. Indigenous populations had the highest level of excess deaths among all ethnic groups. CONCLUSIONS: Overall, the exceptionally high level of excess deaths in Ecuador highlights the enormous burden and heterogeneous impact of COVID-19 on mortality, especially in older age groups and Indigenous populations in Ecuador, which was not fully revealed by COVID-19 death counts. Together with the limited testing in Ecuador, our results suggest that the majority of the excess deaths were likely to be undocumented COVID-19 deaths.

Analysis of Excess Mortality Data at Different Altitudes During the COVID-19 Outbreak in Ecuador.

Ortiz-Prado, Esteban, Raul Patricio Fernandez Naranjo, Eduardo Vasconez, Katherine Simbaña-Rivera, Trigomar Correa-Sancho, Alex Lister, Manuel Calvopiña, and Ginés Viscor. Analysis of excess mortality data at different altitudes during the COVID-19 outbreak in Ecuador. High Alt Med Biol. 22:406-416, 2021. Background: It has been speculated that living at high altitude confers some risk reduction in terms of SARS-CoV-2 infection, reduced transmissibility, and arguable lower COVID-19-related mortality. Objective: We aim to determine the number of excess deaths reported in Ecuador during the first year of the COVID-19 pandemic in relation to different altitude categories among 221 cantons in Ecuador, ranging from sea level to 4,300 m above. Methods: A descriptive ecological country-wide analysis of the excess mortality in Ecuador was performed since March 1, 2020, to March 1, 2021. Every canton was categorized as lower (for altitudes 2,500 m or less) or higher (for altitudes >2,500 m) in a first broad classification, as well as in two different classifications: The one proposed by Imray et al. in 2011 (low altitude <1,500 m, moderate altitude 1,500-2,500 m, high altitude 2,500-3,500 m, or very high altitude 3,500-5,500 m) and the one proposed by Bärtsch et al. in 2008 (near sea level 0-500 m, low altitude 500-2,000 m, moderate altitude 2,000-3,000 m, high altitude 3,000-5,500 m, and extreme altitude 5,500 m). A Poisson fitting analysis was used to identify trends on officially recorded all-caused deaths and those attributed to COVID-19. Results: In Ecuador, at least 120,573 deaths were recorded during the first year of the pandemic, from which 42,453 were catalogued as excessive when compared with the past 3 years of averages (2017-2019). The mortality rate at the lower altitude was 301/100,000 people, in comparison to 242/100,000 inhabitants in elevated cantons. Considering the four elevation categories, the highest excess deaths came from towns located at low altitude (324/100,000), in contrast to the moderate altitude (171/100,000), high-altitude (249/100,000), and very high-altitude (153/100,000) groups. Conclusions: This is the first report on COVID-19 excess mortality in a high-altitude range from 0 to 4,300 m above sea level. We found that absolute COVID-19-related excess mortality is lower both in time and in proportion in the cantons located at high and very high altitude when compared with those cantons located at low altitude.

Estimating and Characterizing COVID-19 Deaths, Puerto Rico, March-July 2020.

OBJECTIVES: Using the Council of State and Territorial Epidemiologists (CSTE) classification guidelines, we characterized coronavirus disease 2019 (COVID-19)-associated confirmed and probable deaths in Puerto Rico during March-July 2020. We also estimated the total number of possible deaths due to COVID-19 in Puerto Rico during the same period. METHODS: We described data on COVID-19-associated mortality, in which the lower bound was the sum of confirmed and probable COVID-19 deaths and the upper bound was excess mortality, estimated as the difference between observed deaths and average expected deaths. We obtained data from the Puerto Rico Department of Health COVID-19 Mortality Surveillance System, the Centers for Disease Control and Prevention's National Electronic Disease Surveillance System Base System, and the National Center for Health Statistics. RESULTS: During March-July 2020, 225 COVID-19-associated deaths were identified in Puerto Rico (119 confirmed deaths and 106 probable deaths). The median age of decedents was 73 (interquartile range, 59-83); 60 (26.7%) deaths occurred in the Metropolitana region, and 140 (62.2%) deaths occurred among men. Of the 225 decedents, 180 (83.6%) had been hospitalized and 93 (41.3%) had required mechanical ventilation. Influenza and pneumonia (48.0%), sepsis (28.9%), and respiratory failure (27.1%) were the most common conditions contributing to COVID-19 deaths based on death certificates. Based on excess mortality calculations, as many as 638 COVID-19-associated deaths could have occurred during the study period, up to 413 more COVID-19-associated deaths than originally reported. CONCLUSIONS: Including probable deaths per the CSTE guidelines and monitoring all-cause excess mortality can lead to a better estimation of COVID-19-associated deaths and serve as a model to enhance mortality surveillance in other US jurisdictions.

Measuring the impact of the COVID-19 outbreak in Ecuador using preliminary estimates of excess mortality, March 17-October 22, 2020.

OBJECTIVES: Ecuador is among the worst-hit countries in the world by the coronavirus disease 2019 (COVID-19) pandemic. In terms of confirmed deaths per million inhabitants, as of October 22, Ecuador ranks fourth in the Americas and ninth worldwide according to data from the World Health Organization. In this report, we estimate excess deaths due to any cause in Ecuador since the start of the lockdown measures on March 17, 2020 until October 22, 2020. METHODS: Estimates of excess deaths were calculated as the difference between the number of observed deaths from all causes and estimates of expected deaths from all causes. Expected deaths were estimated for the period March 17-October 22, 2020 from forecasts of an ARIMA model of order (3,0,1) with drift which was applied to daily mortality data for the period from January 1, 2014 to March 16, 2020. RESULTS: The number of all-cause excess deaths in Ecuador was estimated to be 36,922 (95% bootstrap confidence interval: 32,314-42,696) during the study period. The peak in all-cause excess mortality in Ecuador may have occurred on April 4, 2020, with 909 excess deaths. CONCLUSIONS: Our results suggest that the real impact of the pandemic in Ecuador was much worse than that indicated by reports from national institutions. Estimates of excess mortality might provide a better approximation of the true COVID-19 death toll. These estimates might capture not only deaths directly attributable to the COVID-19 pandemic but also deaths from other diseases that resulted from indirect effects of the pandemic.

Excess mortality in the United States during the first three months of the COVID-19 pandemic.

Deaths are frequently under-estimated during emergencies, times when accurate mortality estimates are crucial for emergency response. This study estimates excess all-cause, pneumonia and influenza mortality during the coronavirus disease 2019 (COVID-19) pandemic using the 11 September 2020 release of weekly mortality data from the United States (U.S.) Mortality Surveillance System (MSS) from 27 September 2015 to 9 May 2020, using semiparametric and conventional time-series models in 13 states with high reported COVID-19 deaths and apparently complete mortality data: California, Colorado, Connecticut, Florida, Illinois, Indiana, Louisiana, Massachusetts, Michigan, New Jersey, New York, Pennsylvania and Washington. We estimated greater excess mortality than official COVID-19 mortality in the U.S. (excess mortality 95% confidence interval (CI) 100 013-127 501 vs. 78 834 COVID-19 deaths) and 9 states: California (excess mortality 95% CI 3338-6344) vs. 2849 COVID-19 deaths); Connecticut (excess mortality 95% CI 3095-3952) vs. 2932 COVID-19 deaths); Illinois (95% CI 4646-6111) vs. 3525 COVID-19 deaths); Louisiana (excess mortality 95% CI 2341-3183 vs. 2267 COVID-19 deaths); Massachusetts (95% CI 5562-7201 vs. 5050 COVID-19 deaths); New Jersey (95% CI 13 170-16 058 vs. 10 465 COVID-19 deaths); New York (95% CI 32 538-39 960 vs. 26 584 COVID-19 deaths); and Pennsylvania (95% CI 5125-6560 vs. 3793 COVID-19 deaths). Conventional model results were consistent with semiparametric results but less precise. Significant excess pneumonia deaths were also found for all locations and we estimated hundreds of excess influenza deaths in New York. We find that official COVID-19 mortality substantially understates actual mortality, excess deaths cannot be explained entirely by official COVID-19 death counts. Mortality reporting lags appeared to worsen during the pandemic, when timeliness in surveillance systems was most crucial for improving pandemic response.

Modeling excess deaths after a natural disaster with application to Hurricane Maria.

Estimation of excess deaths due to a natural disaster is an important public health problem. The CDC provides guidelines to fill death certificates to help determine the death toll of such events. But, even when followed by medical examiners, the guidelines cannot guarantee a precise calculation of excess deaths. We propose two models to estimate excess deaths due to an emergency. The first model is simple, permitting excess death estimation with little data through a profile likelihood method. The second model is more flexible, incorporating temporal variation, covariates, and possible population displacement while allowing inference on how the emergency's effect changes with time. The models are implemented to build confidence intervals estimating Hurricane Maria's death toll.

Excess deaths associated with the 2014 chikungunya epidemic in Jamaica.

Although traditionally chikungunya virus is considered non-fatal, recent studies suggest that there may be in fact underreporting of deaths in some situations. A major chikungunya epidemic hit Jamaica in 2014 but no chikungunya-associated deaths were reported. We assessed the excess of all-cause deaths during this epidemic. Excess deaths were estimated by difference between observed and expected mortality based on the average age-specific mortality rate of 2012-2013, using the 99% confidence interval. There was an excess of 2,499 deaths during the epidemic (91.9/100,000 population), and a strong positive correlation between the monthly incidence of chikungunya and the excess of deaths (Rho = 0.939, p < 0.005). No significant concomitant epidemiological or climatic phenomenon occurred. Chikungunya is a major contributor to morbidity during epidemics and may be an unrecognized cause of death. Thus, it is urgent to review clinical protocols and improve the investigations of specific-cause deaths during chikungunya epidemics. Excess deaths could be a strategic tool for epidemiological surveillance.