Dataset Information

Influenza epidemics, seasonality, and the effects of cold weather on cardiac mortality.

ABSTRACT:

Background

More people die in the winter from cardiac disease, and there are competing hypotheses to explain this. The authors conducted a study in 48 US cities to determine how much of the seasonal pattern in cardiac deaths could be explained by influenza epidemics, whether that allowed a more parsimonious control for season than traditional spline models, and whether such control changed the short term association with temperature.

Methods

The authors obtained counts of daily cardiac deaths and of emergency hospital admissions of the elderly for influenza during 1992-2000. Quasi-Poisson regression models were conducted estimating the association between daily cardiac mortality, and temperature.

Results

Controlling for influenza admissions provided a more parsimonious model with better Generalized Cross-Validation, lower residual serial correlation, and better captured Winter peaks. The temperature-response function was not greatly affected by adjusting for influenza. The pooled estimated increase in risk for a temperature decrease from 0 to -5°C was 1.6% (95% confidence interval (CI) 1.1-2.1%). Influenza accounted for 2.3% of cardiac deaths over this period.

Conclusions

The results suggest that including epidemic data explained most of the irregular seasonal pattern (about 18% of the total seasonal variation), allowing more parsimonious models than when adjusting for seasonality only with smooth functions of time. The effect of cold temperature is not confounded by epidemics.

SUBMITTER: von Klot S

PROVIDER: S-EPMC3517521 | biostudies-literature | 2012 Oct

REPOSITORIES: biostudies-literature

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Publications

Influenza epidemics, seasonality, and the effects of cold weather on cardiac mortality.

von Klot Stephanie S Zanobetti Antonella A Schwartz Joel J

Environmental health : a global access science source 20121001

<h4>Background</h4>More people die in the winter from cardiac disease, and there are competing hypotheses to explain this. The authors conducted a study in 48 US cities to determine how much of the seasonal pattern in cardiac deaths could be explained by influenza epidemics, whether that allowed a more parsimonious control for season than traditional spline models, and whether such control changed the short term association with temperature.<h4>Methods</h4>The authors obtained counts of daily ca ...[more]

PMID: 23025494

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Project description:BackgroundThe survival of coronaviruses are influenced by weather conditions and seasonal coronaviruses are more common in winter months. We examine the seasonality of respiratory infections in England and Wales and the associations between weather parameters and seasonal coronavirus cases.MethodsRespiratory virus disease data for England and Wales between 1989 and 2019 was extracted from the Second-Generation Surveillance System (SGSS) database used for routine surveillance. Seasonal coronaviruses from 2012 to 2019 were compared to daily average weather parameters for the period before the patient's specimen date with a range of lag periods.ResultsThe seasonal distribution of 985,524 viral infections in England and Wales (1989-2019) showed coronavirus infections had a similar seasonal distribution to influenza A and bocavirus, with a winter peak between weeks 2 to 8. Ninety percent of infections occurred where the daily mean ambient temperatures were below 10 °C; where daily average global radiation exceeded 500 kJ/m2/h; where sunshine was less than 5 h per day; or where relative humidity was above 80%. Coronavirus infections were significantly more common where daily average global radiation was under 300 kJ/m2/h (OR 4.3; CI 3.9-4.6; p < 0.001); where average relative humidity was over 84% (OR 1.9; CI 3.9-4.6; p < 0.001); where average air temperature was below 10 °C (OR 6.7; CI 6.1-7.3; p < 0.001) or where sunshine was below 4 h (OR 2.4; CI 2.2-2.6; p < 0.001) when compared to the distribution of weather values for the same time period. Seasonal coronavirus infections in children under 3 years old were more frequent at the start of an annual epidemic than at the end, suggesting that the size of the susceptible child population may be important in the annual cycle.ConclusionsThe dynamics of seasonal coronaviruses reflect immunological, weather, social and travel drivers of infection. Evidence from studies on different coronaviruses suggest that low temperature and low radiation/sunlight favour survival. This implies a seasonal increase in SARS-CoV-2 may occur in the UK and countries with a similar climate as a result of an increase in the R0 associated with reduced temperatures and solar radiation. Increased measures to reduce transmission will need to be introduced in winter months for COVID-19.

Project description:BackgroundInfluenza epidemics have a substantial impact on human health, by increasing the mortality from pneumonia and influenza, respiratory and circulatory diseases, and all causes. This paper provides estimates of excess mortality rates associated with influenza virus circulation for 7 causes of death and 8 age groups in Portugal during the period of 1980-2004.Methodology/principal findingsWe compiled monthly mortality time series data by age for all-cause mortality, cerebrovascular diseases, ischemic heart diseases, diseases of the respiratory system, chronic respiratory diseases, pneumonia and influenza. We also used a control outcome, deaths from injuries. Age- and cause-specific baseline mortality was modelled by the ARIMA approach; excess deaths attributable to influenza were calculated by subtracting expected deaths from observed deaths during influenza epidemic periods. Influenza was associated with a seasonal average of 24.7 all-cause excess deaths per 100,000 inhabitants, approximately 90% of which were among seniors over 65 yrs. Excess mortality was 3-6 fold higher during seasons dominated by the A(H3N2) subtype than seasons dominated by A(H1N1)/B. High excess mortality impact was also seen in children under the age of four years. Seasonal excess mortality rates from all the studied causes of death were highly correlated with each other (Pearson correlation range, 0.65 to 0.95, P<0.001) and with seasonal rates of influenza-like-illness (ILI) among seniors over 65 years (Pearson correlation rho>0.64, P<0.05). By contrast, there was no correlation with excess mortality from injuries.Conclusions/significanceOur excess mortality approach is specific to influenza virus activity and produces influenza-related mortality rates for Portugal that are similar to those published for other countries. Our results indicate that all-cause excess mortality is a robust indicator of influenza burden in Portugal, and could be used to monitor the impact of influenza epidemics in this country. Additional studies are warranted to confirm these findings in other settings.

Dataset Information

Influenza epidemics, seasonality, and the effects of cold weather on cardiac mortality.

Background

Methods

Results

Conclusions

Publications

Influenza epidemics, seasonality, and the effects of cold weather on cardiac mortality.

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