Browse
Submit Data
Databases
API
Help

Dataset Information

9 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

The effect of human settlement temperature and humidity on the growth rules of infected and recovered cases of COVID-19.

ABSTRACT: This study investigated the impact of humidity and temperature on the spread of COVID-19 (SARS-CoV-2) by statistically comparing modelled pandemic dynamics (daily infection and recovery cases) with daily temperature and humidity of three climate zones (Mainland China, South America and Africa) from January to August 2020. We modelled the pandemic growth using a simple logistic function to derive information of the viral infection and describe the growth of infected and recovered cases. The results indicate that the infected and recovered cases of the first wave were controlled in China and managed in both South America and Africa. There is a negative correlation between both humidity (r = - 0.21; p = 0.27) and temperature (r = -0.22; p = 0.24) with spread of the virus. Though this study did not fully encompass socio-cultural factors, we recognise that local government responses, general health policies, population density and transportation could also affect the spread of the virus. The pandemic can be managed better in the second wave if stricter safety protocols are implemented. We urge various units to collaborate strongly and call on countries to adhere to stronger safety protocols in the second wave.

SUBMITTER: Babuna P

PROVIDER: S-EPMC8049428 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

The Influence of Average Temperature and Relative Humidity on New Cases of COVID-19: Time-Series Analysis.

Project description:BackgroundThe influence of meteorological factors on the transmission and spread of COVID-19 is of interest and has not been investigated.ObjectiveThis study aimed to investigate the associations between meteorological factors and the daily number of new cases of COVID-19 in 9 Asian cities.MethodsPearson correlation and generalized additive modeling (GAM) were performed to assess the relationships between daily new COVID-19 cases and meteorological factors (daily average temperature and relative humidity) with the most updated data currently available.ResultsThe Pearson correlation showed that daily new confirmed cases of COVID-19 were more correlated with the average temperature than with relative humidity. Daily new confirmed cases were negatively correlated with the average temperature in Beijing (r=-0.565, P<.001), Shanghai (r=-0.47, P<.001), and Guangzhou (r=-0.53, P<.001). In Japan, however, a positive correlation was observed (r=0.416, P<.001). In most of the cities (Shanghai, Guangzhou, Hong Kong, Seoul, Tokyo, and Kuala Lumpur), GAM analysis showed the number of daily new confirmed cases to be positively associated with both average temperature and relative humidity, especially using lagged 3D modeling where the positive influence of temperature on daily new confirmed cases was discerned in 5 cities (exceptions: Beijing, Wuhan, Korea, and Malaysia). Moreover, the sensitivity analysis showed, by incorporating the city grade and public health measures into the model, that higher temperatures can increase daily new case numbers (beta=0.073, Z=11.594, P<.001) in the lagged 3-day model.ConclusionsThe findings suggest that increased temperature yield increases in daily new cases of COVID-19. Hence, large-scale public health measures and expanded regional research are still required until a vaccine becomes widely available and herd immunity is established.

| S-EPMC7836910 | biostudies-literature

Statistical analysis of the impact of environmental temperature on the exponential growth rate of cases infected by COVID-19.

Project description:We perform a statistical analysis for understanding the effect of the environmental temperature on the exponential growth rate of the cases infected by COVID-19 for US and Italian regions. In particular, we analyze the datasets of regional infected cases, derive the growth rates for regions characterized by a readable exponential growth phase in their evolution spread curve and plot them against the environmental temperatures averaged within the same regions, derive the relationship between temperature and growth rate, and evaluate its statistical confidence. The results clearly support the first reported statistically significant relationship of negative correlation between the average environmental temperature and exponential growth rates of the infected cases. The critical temperature, which eliminates the exponential growth, and thus the COVID-19 spread in US regions, is estimated to be TC = 86.1 ± 4.3 F0.

| S-EPMC7259789 | biostudies-literature

Estimating the parameters of susceptible-infected-recovered model of COVID-19 cases in India during lockdown periods.

Project description:Owing to the pandemic scenario of COVID-19 disease cases all over the world, the outbreak prediction has become extremely complex for the emerging scientific research. Several epidemiological mathematical models of spread are increasing daily to forecast the predictions appropriately. In this study, the classical susceptible-infected-recovered (SIR) modeling approach was employed to study the different parameters of this model for India. This approach was analyzed by considering different governmental lockdown measures in India. Some assumptions were considered to fit the model in the Python simulation for each lockdown scenario. The predicted parameters of the SIR model exhibited some improvement in each case of lockdown in India. In addition, the outcome results indicated that extreme interventions should be performed to tackle this type of pandemic situation in the near future.

| S-EPMC7388782 | biostudies-literature

COVID-19: relationship between atmospheric temperature and daily new cases growth rate.

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.

| S-EPMC7463156 | biostudies-literature

Association between temperature, humidity, and COVID-19 outbreaks in Bangladesh.

Project description:This study aimed to determine the association between average temperature and humidity with COVID-19 pandemic in Bangladesh. This study included 9,455 confirmed cases during the observation period (March 08, 2020 to May 03, 2020). The peak spread of COVID-19 occurred at an average temperature of 26 °C. We find, under a linear regression framework, high temperature and high humidity significantly reduce the transmission of COVID-19, respectively. It indicates that the arrival of summer and rainy season in Bangladesh can effectively reduce the transmission of the COVID-19. However, it is unlikely that the COVID-19 pandemic diminishes by summer since Bangladesh still have a high coronavirus transmission. Therefore, other public health interventions such as social distancing are still important for blocking the COVID-19 transmission.

| S-EPMC7447231 | biostudies-literature

SARS-CoV-2 RNA shedding in recovered COVID-19 cases and the presence of antibodies against SARS-CoV-2 in recovered COVID-19 cases and close contacts, Thailand, April-June 2020.

Project description:Coronavirus disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although Thailand has been fairly effective at controlling the spread of COVID-19, continued disease surveillance and information on antibody response in recovered patients and their close contacts remain necessary in the absence of approved vaccines and antivirals. Here, we examined 217 recovered COVID-19 patients to assess their viral RNA shedding and residual antibodies against SARS-CoV-2. We also evaluated antibodies in blood samples from 308 close contacts of recovered COVID-19 patients. We found that viral RNA remained detectable in 6.6% of recovered COVID-19 cases and up to 105 days. IgM, IgG, and IgA antibodies against SARS-CoV-2 were detected in 13.8%, 88.5%, and 83.4% of the recovered cases 4-12 weeks after disease onset, respectively. Higher levels of antibodies detected were associated with severe illness patients experienced while hospitalized. Fifteen of the 308 contacts (4.9%) of COVID-19 cases tested positive for IgG antibodies, suggesting probable exposure. Viral clearance and the pattern of antibody responses in infected individuals are both crucial for effectively combating SARS-CoV-2. Our study provides additional information on the natural history of this newly emerging disease related to both natural host defenses and antibody duration.

| S-EPMC7595404 | biostudies-literature

Single Cell Analysis of B cells in COVID-19 comprising active and recovered disease

Project description:Using COVID-19 as model, we set out to identify serological, cellular and transcriptomic imprints of pathological responses linked to autoreactive B cells at single-cell resolution

2021-11-02 | E-MTAB-11011 | biostudies-arrayexpress

Effects of temperature and humidity on the spread of COVID-19: A systematic review.

Project description:BACKGROUND:Faced with the global pandemic of COVID-19, declared by World Health Organization (WHO) on March 11th 2020, and the need to better understand the seasonal behavior of the virus, our team conducted this systematic review to describe current knowledge about the emergence and replicability of the virus and its connection with different weather factors such as temperature and relative humidity. METHODS:The review was registered with the PROSPERO database. The electronic databases PubMed, Scopus, Web of Science, Cochrane Library, LILACS, OpenGrey and Google Scholar were examined with the searches restricted to the years 2019 and 2020. Risk of bias assessment was performed using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist tool. The GRADE tool was used to assess the certainty of the evidence. RESULTS:The initial screening identified 517 articles. After examination of the full texts, seventeen studies met the review's eligibility criteria. Great homogeneity was observed in the findings regarding the effect of temperature and humidity on the seasonal viability and transmissibility of COVID-19. Cold and dry conditions were potentiating factors on the spread of the virus. After quality assessment, two studies had a high risk of bias, eleven studies were scored as moderate risk of bias, and four studies were classified as low risk of bias. The certainty of evidence was graded as low for both outcomes evaluated. CONCLUSION:Considering the existing scientific evidence, warm and wet climates seem to reduce the spread of COVID-19. However, these variables alone could not explain most of the variability in disease transmission. Therefore, the countries most affected by the disease should focus on health policies, even with climates less favorable to the virus. Although the certainty of the evidence generated was classified as low, there was homogeneity between the results reported by the included studies.

| S-EPMC7500589 | biostudies-literature

Coronavirus COVID-19 outbreak and control: Effect of temperature, relative humidity, and lockdown implementation.

Project description:Meteorological parameters are important factors that have an influence on infectious diseases. The present study aimed to explore the correlation between the spread of COVID-19, temperature, and relative humidity. The effect of human-imposed control parameters in the form of lockdown on the dissipation of COVID-19 was also analysed. Data were collected on the three study variables - temperature, relative humidity, and lockdown period - from nine of the most infected cities worldwide as well as information on changes in the number of COVID-19 patients from the beginning to a specific point in the lockdown period. A generalised regression model was applied to explore the effect of temperature and relative humidity on the change in daily new cases of COVID-19. The regression analysis did not find any significant correlation between temperature, humidity, and change in number of COVID-19 cases. Analysis of the cities with wide-ranging temperature variations showed a negative correlation of COVID-19 transmission (P=0.079) with temperature, but a relatively non-significant correlation with relative humidity (P=0.198). The number of total deaths was also higher in low-temperature countries compared with high-temperature countries. The specific growth rate in COVID-19 cases was decreased by more than 66% after implementation of a lockdown. This growth rate was exponentially decreased over time through the proper implementation of lockdown. Analysis of the real-case scenario and application of predictive models showed that for New York, Lombardy, and Madrid more than 120 days of strict lockdown was required for complete control of the transmission of COVID-19.

| S-EPMC7755572 | biostudies-literature

Single Cell Multiomics of Healthy, COVID-19 positive and Recovered Individuals

Project description:We performed scRNA sequencing to understand the cellular heterogeneity and immune response landscape behind COVID-19 pathophysiology. We combine this with Ab-Seq, oligo-attached antibody based quantification of cell surface proteins to better understand the cell type and state of the cells. Samples were multiplexed using BD single-cell multiplexing kit (Human) in order to measure these data simultaneously

2022-11-17 | GSE201088 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data