Temperature and precipitation associate with Covid-19 new daily cases: A correlation study between weather and Covid-19 pandemic in Oslo, Norway.
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ABSTRACT:
SUBMITTER: Menebo MM
PROVIDER: S-EPMC7258804 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Meteorological parameters are the critical factors of affecting respiratory infectious disease such as Middle East Respiratory Syndrome (MERS), Severe Acute Respiratory Syndrome (SARS) and influenza, however, the effect of meteorological parameters on coronavirus disease 2019 (COVID-19) remains controversial. This study investigated the effects of meteorological factors on daily new cases of COVID-19 in 127 countries, as of August 31 2020. The log-linear generalized additive model (GAM) was used to analyze the effect of meteorological variables on daily new cases of COVID-19. Our findings revealed that temperature, relative humidity, and wind speed are nonlinearly correlated with daily new cases, and they may be negatively correlated with the daily new cases of COVID-19 over 127 countries when temperature, relative humidity and wind speed were below 20°C, 70% and 7 m/s respectively. Temperature(>20°C) was positively correlated with daily new cases. Wind speed (when>7 m/s) and relative humidity (>70%) was not statistically associated with transmission of COVID-19. The results of this research will be a useful supplement to help healthcare policymakers in the Belt and Road countries, the Centers for Disease Control (CDC) and the World Health Organization (WHO) to develop strategies to combat COVID-19.
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Project description:Daily transcriptomic profiling was conducted on whole blood collected from COVID-19 cases. Whole blood was collected in Tempus Blood RNA tubes, and RNA was extracted from whole blood using the Tempus Spin RNA Isolation Kit. Healthy controls consisted of participants of a measles, mumps and rubella re-vaccination study. Pre-vaccination whole blood was collected and processed and analyzed as above.
2021-02-24 | E-MTAB-9719 | biostudies-arrayexpress
Project description:The emergence of the novel coronavirus has necessitated immense research efforts to understand how several non-environmental and environmental factors affect transmission. With the United States leading the path in terms of case incidence, it is important to investigate how weather variables influence the spread of the disease in the country. This paper assembles a detailed and comprehensive dataset comprising COVID-19 cases and climatological variables for all counties in the continental U.S. and uses a developed econometric approach to estimate the causal effect of certain weather factors on the growth rate of infection. The results indicate a non-linear and significant negative relationship between the individual weather measures and the growth rate of COVID-19 in the U.S. Specifically, the paper finds that a 1 °C rise in daily temperature will reduce daily covid growth rate in the U.S. by approximately 6 percent in the following week, while a marginal increase in relative humidity reduces the same outcome by 1 percent over a similar period. In comparison, a 1 m/s increase in daily wind speed will bring about an 8 percent drop in daily growth rate of COVID-19 in the country. These results differ by location and are robust to several sensitivity checks, so large deviations are unexpected.
| S-EPMC8064870 | biostudies-literature
Project description:Purpose: The novel coronavirus (severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)) first appeared in Wuhan, China, in December 2019, and rapidly spread across the globe. Since most respiratory viruses are known to show a seasonal pattern of infection, it has been hypothesised that SARS-CoV-2 may be seasonally dependent as well. The present study looks at a possible effect of atmospheric temperature, which is one of the suspected factors influencing seasonality, on the evolution of the pandemic. Basic procedures: Since confirming a seasonal pattern would take several more months of observation, we conducted an innovative day-to-day micro-correlation analysis of nine outbreak locations, across four continents and both hemispheres, in order to examine a possible relationship between atmospheric temperature (used as a proxy for seasonality) and outbreak progression. Main findings: There was a negative correlation between atmospheric temperature variations and daily new cases growth rates, in all nine outbreaks, with a median lag of 10 days. Principal conclusions: The results presented here suggest that high temperatures might dampen SARS-CoV-2 propagation, while lower temperatures might increase its transmission. Our hypothesis is that this could support a potential effect of atmospheric temperature on coronavirus disease progression, and potentially a seasonal pattern for this virus, with a peak in the cold season and rarer occurrences in the summer. This could guide government policy in both the Northern and Southern hemispheres for the months to come.
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Project description:Weather forecasts play essential parts in economic activity. Assimilation of meteorological observations from aircraft improves forecasts greatly. However, global lockdown during the COVID-19 pandemic (March to May 2020) has eliminated 50-75% aircraft observations and imperiled weather forecasting. Here, we verify global forecasts against reanalysis to quantify the impact of the pandemic. We find a large deterioration in forecasts of surface meteorology over regions with busy air flights, such as North America, southeast China, and Australia. Forecasts over remote regions are also substantially worse during March to May 2020 than 2017-2019, and the deterioration increases for longer-term forecasts. This could handicap early warning of extreme weather and cause additional economic damage on the top of that from the pandemic. The impact over Western Europe is buffered by the high density of conventional observations, suggesting that introduction of new observations in data-sparse regions would be needed to minimize the impact of global emergencies on weather forecasts.
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Project description:BackgroundNorway and Sweden have similar populations and health care systems, but different reactions to the COVID-19 pandemic. Norway closed educational institutions, and banned sports and cultural activities; Sweden kept most institutions and training facilities open. We aimed to compare peoples' attitudes towards authorities and control measures, and perceived impact of the pandemic and implemented control measures on life in Norway and Sweden.MethodsAnonymous web-based surveys for individuals age 15 or older distributed through Facebook using the snowball method, in Norway and Sweden from mid-March to mid-April, 2020. The survey contained questions about perceived threat of the pandemic, views on infection control measures, and impact on daily life. We performed descriptive analyses of the responses and compared the two countries.Results3508 individuals participated in the survey (Norway 3000; Sweden 508). 79% were women, the majority were 30-49 years (Norway 60%; Sweden 47%), and about 45% of the participants in both countries had more than 4 years of higher education. Participants had high trust in the health services, but differed in the degree of trust in their government (High trust in Norway 17%; Sweden 37%). More Norwegians than Swedes agreed that school closure was a good measure (Norway 66%; Sweden 18%), that countries with open schools were irresponsible (Norway 65%; Sweden 23%), and that the threat from repercussions of the mitigation measures were large or very large (Norway 71%; Sweden 56%). Both countries had a high compliance with infection preventive measures (> 98%). Many lived a more sedentary life (Norway 69%; Sweden 50%) and ate more (Norway 44%; Sweden 33%) during the pandemic.ConclusionSweden had more trust in the authorities, while Norwegians reported a more negative lifestyle during the pandemic. The level of trust in the health care system and self-reported compliance with preventive measures was high in both countries despite the differences in infection control measures.
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Project description:Projections of the near future of daily case incidence of COVID-19 are valuable for informing public policy. Near-future estimates are also useful for outbreaks of other diseases. Short-term predictions are unlikely to be affected by changes in herd immunity. In the absence of major net changes in factors that affect reproduction number (R), the two-parameter exponential model should be a standard model â€" indeed, it has been standard for epidemiological analysis of pandemics for a century but in recent decades has lost popularity to more complex compartmental models. Exponential models should be routinely included in reports describing epidemiological models as a reference, or null hypothesis. Exponential models should be fitted separately for each epidemiologically distinct jurisdiction. They should also be fitted separately to time intervals that differ by any major changes in factors that affect R. Using an exponential model, incidence-count half-life ( t 1/2 ) is a better statistic than R. Here an example of the exponential model is applied to King County, Washington during Spring 2020. During the pandemic, the parameters and predictions of this model have remained stable for intervals of one to four months, and the accuracy of model predictions has outperformed models with more parameters. The COVID pandemic can be modeled as a series of exponential curves, each spanning an interval ranging from one to four months. The length of these intervals is hard to predict, other than to extrapolate that future intervals will last about as long as past intervals.
| S-EPMC9216716 | biostudies-literature
Project description:Rising temperature levels during spring and summer are often argued to enable lifting of strict containment measures even in the absence of herd immunity. Despite broad scholarly interest in the relationship between weather and coronavirus spread, previous studies come to very mixed results. To contribute to this puzzle, the paper examines the impact of weather on the COVID-19 pandemic using a unique granular dataset of over 1.2 million daily observations covering over 3700 counties in nine countries for all seasons of 2020. Our results show that temperature and wind speed have a robust negative effect on virus spread after controlling for a range of potential confounding factors. These effects, however, are substantially larger during mealtimes, as well as in periods of high mobility and low containment, suggesting an important role for social behaviour.
| S-EPMC8585954 | biostudies-literature
Project description:BackgroundThai massage is a highly gendered and culturally specific occupation. Many female Thai masseuses migrate to Norway as marriage migrants and as such are entitled to the same public healthcare as Norwegian citizens. Additionally, anyone who is not fluent in Norwegian is entitled to have an interpreter provided by the public healthcare system. Norway and most other countries aspire to universal health coverage, but certain immigrant populations continue to experience difficulties accessing appropriate healthcare. This study examined healthcare access among Thai migrant masseuses in Oslo.MethodsGuided by access to healthcare theory, we conducted a qualitative exploratory study in 2018 with Thai women working as masseuses in Oslo, Norway. Through semi-structured in-depth interviews with 14 Thai women, we explored access to healthcare, health system navigation and care experiences. We analyzed the data using thematic analysis and grouped the information into themes relevant to healthcare access.ResultsParticipants did not perceive that their occupation limited their access to healthcare. Most of the barriers participants experienced when accessing care were related to persistent language challenges. Women who presented at healthcare facilities with their Norwegian spouse were rarely offered interpreters, despite their husband's limited capacity to translate effectively. Cultural values inhibit women from demanding the interpretation services to which they are entitled. In seeking healthcare, women sought information about health services from their Thai network and relied on family members, friends and contacts to act as informal interpreters. Some addressed their healthcare needs through self-treatment using imported medication or sought healthcare abroad.ConclusionsDespite having the same entitlements to public healthcare as Norwegian citizens, Thai migrants experience difficulties accessing healthcare due to pervasive language barriers. A significant gap exists between the official policy that professional interpreters should be provided and the reality experienced by study participants. To improve communication and equitable access to healthcare for Thai immigrant women in Norway, health personnel should offer professional interpreters and not rely on Norwegian spouses to translate. Use of community health workers and outreach through Thai networks, may also improve Thai immigrants' knowledge and ability to navigate the Norwegian healthcare system.
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Project description:Coronavirus disease 2019 (COVID-19), a global pandemic, has caused over 216 million cases and 4.50 million deaths as of 30 August 2021. Vaccines can be regarded as one of the most powerful weapons to eliminate the pandemic, but the impact of vaccines on daily COVID-19 cases and deaths by country is unclear. This study aimed to investigate the correlation between vaccines and daily newly confirmed cases and deaths of COVID-19 in each country worldwide. Daily data on firstly vaccinated people, fully vaccinated people, new cases and new deaths of COVID-19 were collected from 187 countries. First, we used a generalized additive model (GAM) to analyze the association between daily vaccinated people and daily new cases and deaths of COVID-19. Second, a random effects meta-analysis was conducted to calculate the global pooled results. In total, 187 countries and regions were included in the study. During the study period, 1,011,918,763 doses of vaccine were administered, 540,623,907 people received at least one dose of vaccine, and 230,501,824 people received two doses. For the relationship between vaccination and daily increasing cases of COVID-19, the results showed that daily increasing cases of COVID-19 would be reduced by 24.43% [95% CI: 18.89, 29.59] and 7.50% [95% CI: 6.18, 8.80] with 10,000 fully vaccinated people per day and at least one dose of vaccine, respectively. Daily increasing deaths of COVID-19 would be reduced by 13.32% [95% CI: 3.81, 21.89] and 2.02% [95% CI: 0.18, 4.16] with 10,000 fully vaccinated people per day and at least one dose of vaccine, respectively. These findings showed that vaccination can effectively reduce the new cases and deaths of COVID-19, but vaccines are not distributed fairly worldwide. There is an urgent need to accelerate the speed of vaccination and promote its fair distribution across countries.
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