Author：K. Kály-Kullai

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Journal：Physiology International

Publishing Time： 1-11

DOI：10.1556/2060.2020.00015

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Journal：科学

Publishing Time：

DOI：10.1126/science.abb7234

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Journal：Environmental Engineering Science

Publishing Time：

DOI：10.1089/ees.2020.0096

Author：Yongjian Zhu

Abstract：Background: Coronavirus disease 2019 (COVID-19) has become a severe public health problem globally. Both epidemiological and laboratory studies have shown that ambient temperature could affect the transmission and survival of coronaviruses. This study aimed to determine whether the temperature is an essential factor in the infection caused by this novel coronavirus. Methods: Daily confirmed cases and meteorological factors in 122 cities were collected between January 23, 2020, to February 29, 2020. A generalized additive model (GAM) was applied to explore the nonlinear relationship between mean temperature and COVID-19 confirmed cases. We also used a piecewise linear regression to determine the relationship in detail. Results: The exposure-response curves suggested that the relationship between mean temperature and COVID-19 confirmed cases was approximately linear in Journal Pre-proof Journal Pre-proof the range of less than 3 °C and became flat above 3 °C. When mean temperature (lag0-14) was below 3 °C, each 1 °C rise was associated with a 4.861% (95% CI: 3.209-6.513) increase in the daily number of COVID-19 confirmed cases. These findings were robust in our sensitivity analyses. Conclusions: Our results indicate that mean temperature has a positive linear relationship with the number of COVID-19 cases with a threshold of 3 °C. There is no evidence supporting that case counts of COVID-19 could decline when the weather becomes warmer, which provides useful implications for policymakers and the public.

Journal：Science of the Total Environment

Publishing Time：S0048-9697(20)31714-9

DOI：10.1016/j.scitotenv.2020.138201

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Journal：工作暴露与健康年刊

Publishing Time：

DOI：10.1093/annweh/wxaa024

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Journal：旅游医学与传染病

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DOI：10.1016/j.tmaid.2020.101630

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Journal：新英格兰医学杂志

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DOI：10.1056/NEJMc2004973

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Journal：Irish journal of medical science

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DOI：10.1007/s11845-020-02218-2

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Journal：World Chinese Medicine

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DOI：

Author：SU Liyun

Abstract： Novel coronavirus pneumonia (COVID-19) spreads quickly. We need to have an accurate understanding of the cumulative confirmed count in various provinces in China. The static spatial distribution and dynamic evolution of the cumulative confirmed count in various provinces in China are revealed by using spatial statistical analysis. The data of the cumulative confirmed count from January 26th, 2020 to February 20th, 2020, from the outbreak to the control of the virus, is analyzed. The results show the cumulative confirmed count of each province in China has a positive spatial correlation before February 3th, a negative spatial correlation from February 3th to February 11th, and a random distribution in space after February 11th. Looking at the characteristics of local aggregation in different provinces, the high-low clustering occurs mainly in Hubei, while the low-high clustering mainly in provinces around Hubei. And provinces far from Hubei are low-low pattern. And the provinces with significant high-low clustering and low-high clustering gradually increase.

Journal：ournal of Chongqing University of Technology(Natural Science)

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DOI：

Author：Andrew J. Stier

Abstract：The current outbreak of novel coronavirus disease 2019 (COVID-19) poses an unprecedented global health and economic threat to interconnected human so_x0002_cieties. Until a vaccine is developed, strategies for controlling the outbreak rely on aggressive social distancing. These measures largely disconnect the social network fabric of human societies, especially in urban areas. Here, we estimate the growth rates and reproductive numbers of COVID-19 in US cities from March 14th through March 19th to reveal a power-law scaling relationship to city population size. This means that COVID-19 is spreading faster on average in larger cities with the additional implication that, in an uncontrolled outbreak, larger fractions of the population are expected to become infected in more populous urban areas. We discuss the implications of these observations for controlling the COVID-19 outbreak, emphasizing the need to implement more aggressive distancing policies in larger cities while also with preserving socioeconomic activity.

Journal：arxiv

Publishing Time：eprint

DOI：arXiv:2003.10376

Author：Mohammad M. Sajadi

Abstract：A significant number of infectious diseases display seasonal patterns in their incidence, including human coronaviruses. We hypothesize that SARS-CoV-2 does as well. To date, Coronavirus Disease 2019 (COVID-19), caused by SARS-CoV-2, has established significant community spread in cities and regions only along a narrow east west distribution roughly along the 30-50 N” corridor at consistently similar weather patterns (5-11OC and 47-79% humidity). There has been a lack of significant community establishment in expected locations that are based only on population proximity and extensive population interaction through travel. We have proposed a simplified model that shows a zone at increased risk for COVID-19 spread. Using weather modeling, it may be possible to predict the regions most likely to be at higher risk of significant community spread of COVID-19 in the upcoming weeks, allowing for concentration of public health efforts on surveillance and containment.

Journal：SSRN

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Author：Richard A. Neher

Abstract：A novel coronavirus (SARS-CoV-2) first detected in Wuhan, China, has spread rapidly since December 2019, causing more than 80,000 confirmed infections and 2,700 fatalities (as of Feb 27, 2020). Imported cases and transmission clusters of various sizes have been reported globally suggesting a pandemic is likely. Here, we explore how seasonal variation in transmissibility could modulate a SARS-CoV-2 pandemic. Data from routine diagnostics show a strong and consistent seasonal variation of the four endemic coronaviruses (229E, HKU1, NL63, OC43) and we parameterize our model for SARS-CoV-2 using these data. The model allows for many subpopulations of different size with variable parameters. Simulations of different scenarios show that plausible parameters result in a small peak in early 2020 in temperate regions of the Northern Hemisphere and a larger peak in winter 2020/2021. Variation in transmission and migration rates can result in substantial variation in prevalence between regions. While the uncertainty in parameters is large, the scenarios we explore show that transient reductions in the incidence rate might be due to a combination of seasonal variation and infection control efforts but do not necessarily mean the epidemic is contained. Seasonal forcing on SARS-CoV-2 should thus be taken into account in the further monitoring of the global transmission. The likely aggregated effect of seasonal variation, infection control measures and transmission rate variation is a prolonged pandemic wave with lower prevalence at any given time, thereby providing a window of opportunity for better preparation of health care systems.

Journal：medrxiv

Publishing Time：

DOI：10.1101/2020.02.13.20022806