Impact of non-pharmaceutical interventions, weather, vaccination, and variants on COVID-19 transmission across departments in France

BMC Infectious Diseases, Journal Year: 2023, Volume and Issue: 23(1)

Published: March 30, 2023

Multiple factors shape the temporal dynamics of COVID-19 pandemic. Quantifying their relative contributions is key to guide future control strategies. Our objective was disentangle individual effects non-pharmaceutical interventions (NPIs), weather, vaccination, and variants concern (VOC) on local SARS-CoV-2 transmission.We developed a log-linear model for weekly reproduction number (R) hospital admissions in 92 French metropolitan departments. We leveraged (i) homogeneity data collection NPI definitions across departments, (ii) spatial heterogeneity timing NPIs, (iii) an extensive observation period (14 months) covering different weather conditions, VOC proportions, vaccine coverage levels.Three lockdowns reduced R by 72.7% (95% CI 71.3-74.1), 70.4% (69.2-71.6) 60.7% (56.4-64.5), respectively. Curfews implemented at 6/7 pm 8/9 34.3% (27.9-40.2) 18.9% (12.04-25.3), School closures only 4.9% (2.0-7.8). estimated that vaccination entire population would have 71.7% (56.4-81.6), whereas emergence (mainly Alpha during study period) increased transmission 44.6% (36.1-53.6) compared with historical variant. Winter conditions (lower temperature absolute humidity) 42.2% (37.3-47.3) summer conditions. Additionally, we explored counterfactual scenarios (absence or vaccination) assess impact admissions.Our demonstrates strong effectiveness NPIs quantifies role while adjusting other confounders. It highlights importance retrospective evaluation inform decision-making.

Language: Английский

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Cold and dry winter conditions are associated with greater SARS-CoV-2 transmission at regional level in western countries during the first epidemic wave

Scientific Reports, Journal Year: 2021, Volume and Issue: 11(1)

Published: June 17, 2021

Abstract Higher transmissibility of SARS-CoV-2 in cold and dry weather conditions has been hypothesized since the onset COVID-19 pandemic but level epidemiological evidence remains low. During first wave pandemic, Spain, Italy, France, Portugal, Canada USA presented an early spread, a heavy burden, low initial public health response until lockdowns. In context when testing was limited, we calculated basic reproduction number (R 0 ) 63 regions from growth regional death counts. After adjusting for population density, spread epidemic, age structure, temperature humidity were negatively associated with transmissibility. A reduction mean absolute by 1 g/m 3 0.15-unit increase R . Below 10 °C, °C 0.16-unit Our results confirm dependency to absence control measures during wave. The transition summer winter, corresponding drop overall decrease humidity, likely contributed intensification second north-west hemisphere countries. Non-pharmaceutical interventions must be adjusted account increased winter conditions.

Language: Английский

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One-Year Lesson: Machine Learning Prediction of COVID-19 Positive Cases with Meteorological Data and Mobility Estimate in Japan

International Journal of Environmental Research and Public Health, Journal Year: 2021, Volume and Issue: 18(11), P. 5736 - 5736

Published: May 27, 2021

With the wide spread of COVID-19 and corresponding negative impact on different life aspects, it becomes important to understand ways deal with pandemic as a part daily routine. After year pandemic, has become obvious that factors, including meteorological influence speed at which disease is potential fatalities. However, each factor spreading remains controversial. Accurate forecasting positive cases may lead better management healthcare resources provide guidelines for government policies in terms action required within an effective timeframe. Recently, Google Cloud provided online data United States Japan, would help predicting future situations state/prefecture scale are updated day-by-day basis. In this study, we propose deep learning architecture predict considering various such public mobility estimates, applied collected Japan demonstrate its effectiveness. The proposed model was constructed using neural network based long short-term memory (LSTM) network. consists multi-path LSTM layers trained time-series obtained from open-source data. tested time frames, results were compared forecasts. Public dominant estimating new cases, whereas improve their accuracy. average relative error ranged 16.1% 22.6% major regions, significant improvement forecasting. This can be used awareness regarding morbidity risk feasible manner.

Language: Английский

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Green-Blue Spaces and Population Density versus COVID-19 Cases and Deaths in Poland

International Journal of Environmental Research and Public Health, Journal Year: 2021, Volume and Issue: 18(12), P. 6636 - 6636

Published: June 20, 2021

In the last year, in connection with COVID-19 pandemic caused by SARS-CoV-2 coronavirus, scientific papers have appeared which authors are trying to identify factors (including environmental) favoring spread of this disease. This paper presents spatial differentiation total number cases and deaths during full year (March 2020-March 2021) Poland versus green-blue spaces (green-i.a. forests, orchards, meadows pastures, recreational rest areas, biologically active arable land; blue-lakes artificial water reservoirs, rivers, ecological areas internal waters) population density. The analysis covers 380 counties, including 66 cities. study used daily reports on progress published Ministry Health Republic unique, detailed data 24 types land use available Statistics database. Statistical relationships were determined between above-mentioned environmental variables characterizing (cases deaths). Various basic regression models analysed. optimal model was selected, determination coefficient, significance level values parameters these relationships, together estimation error, calculated. obtained results indicated that higher individual lower infections deaths. These described logarithmic homographic models. turn, an increase density deaths, according power model. can be current pandemic, location potential outbreaks. developed as a tool forecasting development making decisions about implementation preventive measures.

Language: Английский

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SARS-CoV-2 seroprevalence around the world: an updated systematic review and meta-analysis

European journal of medical research, Journal Year: 2022, Volume and Issue: 27(1)

Published: June 2, 2022

Covid-19 has been one of the major concerns around world in last 2 years. One challenges this disease to determine its prevalence. Conflicting results serology test Covid explored need for an updated meta-analysis on issue. Thus, systematic review aimed estimate prevalence global SARS-CoV-2 different populations and geographical areas.To identify studies evaluating seroprevalence SARS-CoV-2, a comprehensive literature search was performed from international databases, including Medline (PubMed), Web Sciences, Scopus, EMBASE, CINHAL.In meta-analysis, showed that is between 3 15% worldwide. In Eastern Mediterranean, pooled (CI 95% 5-29%), Africa, 6% 1-13%). America, 8% 6-11%), Europe, 5% 4-6%). Also region, Western Pacific, 3% 2-4%). Besides, we analyzed three these areas separately. This analysis estimated subgroups such as study population, diagnostic methods, sampling time, perspective, type study.The present Even considering low rate increasing vaccination world, many people are still susceptible SARS-CoV-2.

Language: Английский

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