Abstract
Although much progress has been made to uncover age-specific mortality patterns of the 1918 influenza pandemic in populations around the world, more studies in different populations are ...needed to make sense of the heterogeneous death impact of this pandemic. We assessed the absolute and relative magnitudes of 3 pandemic waves in the city of Madrid, Spain, between 1918 and 1920, on the basis of age-specific all-cause and respiratory excess death rates. Excess death rates were estimated using a Serfling model with a parametric bootstrapping approach to calibrate baseline death levels with quantified uncertainty. Excess all-cause and pneumonia and influenza mortality rates were estimated for different pandemic waves and age groups. The youngest and oldest persons experienced the highest excess mortality rates, and young adults faced the highest standardized mortality risk. Waves differed in strength; the peak standardized mortality risk occurred during the herald wave in spring 1918, but the highest excess rates occurred during the fall and winter of 1918/1919. Little evidence was found to support a “W”-shaped, age-specific excess mortality curve. Acquired immunity may have tempered a protracted fall wave, but recrudescent waves following the initial 2 outbreaks heightened the total pandemic mortality impact.
Analyses of health and mortality disparities between today's urban and rural populations appear to be exclusively focused on vastly urbanising countries. By incorporating environmental data at census ...tract level and accounting for within‐area homogeneity, this work attempts to extend classic rural–urban comparisons. Geographical information is linked to a register‐based mortality follow up and Spanish census data for the autonomous community of Andalusia. We then apply mixed effects Cox proportional hazards models to estimate individual mortality differences and account for area variations between residential areas. Estimated effects suggest that the shared degree of “urbanicity” does not affect individual hazards of mortality, whereas environmental‐ and population‐based measures influence the relative risk of dying despite controlling for individual‐level risk factors. Although we do not find an impact of physical urban measures, our results reveal persistent that area‐related mortality disparities which can help to explain the mechanisms behind prevalent spatial‐temporal inequalities such as those in Andalusia.
Although the 1889–1890 influenza pandemic was one of the most important epidemic events of the 19th century, little is known about the mortality impact of this pandemic based on detailed respiratory ...mortality data sets.
We estimated excess mortality rates for the 1889–1890 pandemic in Madrid from high-resolution respiratory and all-cause individual-level mortality data retrieved from the Gazeta de Madrid, the Official Bulletin of the Spanish government. We also generated estimates of the reproduction number from the early growth phase of the pandemic.
The main pandemic wave in Madrid was evident from respiratory and all-cause mortality rates during the winter of 1889–1890. Our estimates of excess mortality for this pandemic were 58.3 per 10,000 for all-cause mortality and 44.5 per 10,000 for respiratory mortality. Age-specific excess mortality rates displayed a J-shape pattern, with school children aged 5–14 years experiencing the lowest respiratory excess death rates (8.8 excess respiratory deaths per 10,000), whereas older populations aged greater than or equal to 70 years had the highest rates (367.9 per 10,000). Although seniors experienced the highest absolute excess death rates, the standardized mortality ratio was highest among young adults aged 15–24 years. The early growth phase of the pandemic displayed dynamics consistent with an exponentially growing transmission process. Using the generalized-growth method, we estimated the reproduction number in the range of 1.2–1.3 assuming a 3-day mean generation interval and of 1.3–1.5 assuming a 4-day mean generation interval.
Our study adds to our understanding of the mortality impact and transmissibility of the 1889–1890 influenza pandemic using detailed individual-level mortality data sets. More quantitative studies are needed to quantify the variability of the mortality impact of this understudied pandemic at regional and global scales.
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