how does the coronavirus respond to changes in the weather

We don't know if changing seasons will help stem the outbreak, says Michael Le Page

Will heat kill the coronavirus?

BACKGROUND: There is sufficient epidemiological and biological evidence of increased human susceptibility to viral pathogens such as Middle East respiratory syndrome coronavirus, respiratory syncytial virus, human metapneumovirus and influenza virus, in cold weather. The pattern of outbreak of the coronavirus disease 2019 (COVID-19) in China during the flu season is further proof that meteorological conditions may potentially influence the susceptibility of human populations to coronaviruses, a situation that may become increasingly evident as the current global pandemic of COVID-19 unfolds. MAIN BODY: A very rapid spread and high mortality rates have characterized the COVID-19 pandemic in countries north of the equator where air temperatures have been seasonally low. It is unclear if the currently high rates of COVID-19 infections in countries of the northern hemisphere will wane during the summer months, or if fewer people overall will become infected with COVID-19 in countries south of the equator where warmer weather conditions prevail through most of the year. However, apart from the influence of seasons, evidence based on the structural biology and biochemical properties of many enveloped viruses similar to the novel severe acute respiratory syndrome coronavirus 2 or SARS-CoV-2 (aetiology of COVID-19), support the higher likelihood of the latter of the two outcomes. Other factors that may potentially impact the rate of virus spread include the effectiveness of infection control practices, individual and herd immunity, and emergency preparedness levels of countries. CONCLUSION: This report highlights the potential influence of weather conditions, seasons and non-climatological factors on the geographical spread of cases of COVID-19 across the globe.

A close look at the biology of SARS-CoV-2, and the potential influence of weather conditions and seasons on COVID-19 case spread

Objective: To investigate the meteorological condition for incidence and spread of 2019-nCoV infection, to predict the epidemiology of the infectious disease, and to provide a scientific basis for prevention and control measures against the new disease. Methods: The meteorological factors during the outbreak period of the novel coronavirus pneumonia in Wuhan in 2019 were collected and analyzed, and were confirmed with those of Severe Acute Respiratory Syndrome (SARS) in China in 2003. Data of patients infected with 2019-nCoV and SARS coronavirus were collected from WHO website and other public sources. Results: This study found that the suitable temperature range for 2019-nCoV coronavirus survival is (13-24 degree Celsius), among which 19 degree Celsius lasting about 60 days is conducive to the spread between the vector and humans; the humidity range is 50%-80%, of which about 75% humidity is conducive to the survival of the coronavirus; the suitable precipitation range is below 30 mm/ month. Cold air and continuous low temperature over one week are helpful for the elimination of the virus. The prediction results show that with the approach of spring, the temperature in north China gradually rises, and the coronavirus spreads to middle and high latitudes along the temperature line of 13-18 degree Celsius. The population of new coronavirus infections is concentrated in Beijing, Tianjin, Hebei, Jiangsu, Zhejiang, Shanghai and other urban agglomerations. Starting from May 2020, the Beijing-Tianjin-Hebei urban agglomeration, the Central China Zhengzhou-Wuhan urban agglomeration, the eastern Jiangsu-Zhejiang-Shanghai urban agglomeration, and the southern Pearl River Delta urban agglomeration are all under a high temperature above 24 degree Celsius, which is not conducive to the survival and reproduction of coronaviruses, so the epidemic is expected to end. Conclusions: A wide range of continuous warm and dry weather is conducive to the survival of 2019-nCoV. The coming of spring, in addition to the original Wuhan-Zhengzhou urban agglomeration in central China, means that the prevention and control measures in big cities located in mid-latitude should be strengthened, especially the monitoring of transportation hubs. The Pearl River Delta urban agglomeration is a concentrated area of population in south China, with a faster temperature rise than those in mid-high latitudes, and thus the prevention in this area should be prioritized. From a global perspective, cities with a mean temperature below 24 degree Celsius are all high-risk cities for 2019-nCoV transmission before June.

Analysis of meteorological conditions and prediction of epidemic trend of 2019-nCoV infection in 2020

Do Humidity and Temperature Impact the Spread of the Novel Coronavirus?

Predicting COVID-19 epidemic development in the upcoming warm season has attracted much attention in the hope of providing helps to fight the epidemic. It requires weather (environmental) factors to be included in prediction models, but there are few models to achieve it successfully. In this study, we proposed a new concept of environmental infection rate (RE), based on floating time of respiratory droplets in the air and inactivation rate of virus to solve the problem. More than half of the particles in the droplets can float in the atmosphere for 1-2 hours. The prediction results showed that high RE values (>3.5) are scattered around 30N in winter (Dec.-Feb.). As the weather warms, its distribution area expands and extends to higher latitudes of northern hemisphere, reaching its maximum in April, and then shrinking northward. These indicated that the spread of COVID-19 in most parts of the northern hemisphere is expected to decline after Apr., but the risks in high latitudes will remain high in May. In the south of southern hemisphere, the RE values tend to subside from Apr. to July. The high modeled RE values up to July, however, suggested that warmer weather will not stop COVID-19 from spreading. Public health intervention is needed to overcome the outbreak.

Warmer weather and global trends in the coronavirus COVID-19

(1) Background: The virulence of coronavirus diseases due to viruses like SARS-CoV or MERS-CoV decreases in humid and hot weather. The putative temperature dependence of infectivity by the new coronavirus SARS-CoV-2 or covid-19 has a high predictive medical interest. (2) Methods: External temperature and new covid-19 cases in 21 countries and in the French administrative regions were collected from public data. Associations between epidemiological parameters of the new case dynamics and temperature were examined using an ARIMA model. (3) Results: We show that, in the first stages of the epidemic, the velocity of contagion decreases with country- or region-wise temperature. (4) Conclusions: Results indicate that high temperatures diminish initial contagion rates, but seasonal temperature effects at later stages of the epidemy remain questionable. Confinement policies and other eviction rules should account for climatological heterogeneities, in order to adapt the public health decisions to possible geographic or seasonal gradients.

Temperature Decreases Spread Parameters of the New Covid-19 Case Dynamics

Coronavirus spread is more serious in urban metropolitan cities compared to rural areas. It is observed from the data on the infection rate available in the various sources that the cold and dry conditions accelerate the spread of coronavirus. In the present work, the existing theory of respiratory droplet drying is used to propose the mechanism of virus spread under various climates and the indoor environment conditions which plays a greater role in the virus spread. This concept is assessed using four major parameters such as population density, climate severity, the volume of indoor spaces, and air-conditioning usage which affect the infection spread and mortality using the data available for various states of India. Further, it is analysed using the data from various states in India along with the respective climatic conditions. It is found that under some indoor scenarios, the coronaviruses present in the respiratory droplets become active due to size reduction that occurs both in sessile and airborne droplet nuclei causing an increase in the spread. Understanding this mechanism will be very useful to take the necessary steps to reduce the rate of transmission by initiating corrective measures and maintaining the required conditions in the indoor built environment.

The contribution of dry indoor built environment on the spread of Coronavirus: Data from various Indian states

Pandemic enveloped RNA Novel Corona Virus' 2019 (SARS-CoV-2) appears as a beating reed which induce overwhelming outbreak all over the world since November 2019 to till date. Inherent Immunity developed by traditional food habit, exposure to various antigens and vitamin D induced sunlight exposure. Meteorological parameters are the important factors which influencing the severe acute respiratory syndrome (SARS) like infectious disease. Aim of this review to enhance our knowledge and explore the association among build up immunity, weather parameters and Corona virus disease (COVID-19) death. In this review we emphasize role of meteorological factor included degree of sun exposure and effect of temperature on enveloped lipid bi-layer structure of Novel corona virus. These meteorological factors and inherent immunity may have impact on SARS-CoV-2 incidence among South East Asian including Bangladeshi. In summary, this study suggests that temperature-humidity variation, inherent immunity and lower life expectancy of South East Asia may be important.

Sub-continental Atmosphere and Inherent Immune System may have Impact on Novel Corona Virus' 2019 (nCovid-19) Prevalence in South East Asia.

The new coronavirus, called 2019-nCoV, is a new type of virus that was first identified in Wuhan, China, in December 2019. Environmental conditions necessary for survival and spread of 2019-nCoV are somewhat transparent but unlike animal coronaviruses. We are poorly aware of their survival in environment and precise factors of their transmission. Countries located in east and west of globe did not have a significant impact on prevalence of disease among communities, and on the other hand, north and south have provided a model for relative prediction of disease outbreaks. The 2019-nCoV can survive for up to 9 days at 25 °C, and if this temperature rises to 30 °C, its lifespan will be shorter. The 2019-nCoV is sensitive to humidity, and lifespan of viruses in 50% humidity is longer than that of 30%. Also, temperature and humidity are important factors influencing the COVID-19 mortality rate and may facilitate 2019-nCoV transmission. Thus, considering the available and recent evidence, it seems that low temperatures, as well as dry and unventilated air, may affect stability and transmissibility of 2019-nCoV.

Environmental concern regarding the effect of humidity and temperature on 2019-nCoV survival: fact or fiction

The COVID-19 pandemic has affected most countries of the world. As corona viruses are highly prevalent in the cold season, the question remains whether or not the pandemic will improve with increasing temperatures in the Northern hemisphere. We use data from a primary care registry of almost 15,000 patients over 20 years to retrieve information on viral respiratory infection outbreaks. Our analysis suggests that the severity of the pandemic will be softened by the seasonal change to summer.

Will the COVID-19 pandemic slow down in the Northern hemisphere by the onset of summer? An epidemiological hypothesis

The undefendable outbreak of novel coronavirus (SARS-COV-2) lead to a global health emergency due to its higher transmission rate and longer symptomatic duration, created a health surge in a short time. Since Nov 2019 the outbreak in China, the virus is spreading exponentially everywhere. The current study focuses on the relationship between environmental parameters and the growth rate of COVID-19. The statistical analysis suggests that the temperature changes retarded the growth rate and found that -6.28{degrees}C and +14.51{degrees}C temperature is the favorable range for COVID-19 growth. Gutenberg- Richter's relationship is used to estimate the mean daily rate of exceedance of confirmed cases concerning the change in temperature. Temperature is the most influential parameter that reduces the growth at the rate of 13-16 cases/day with a 1{degrees}C rise in temperature.

Does weather affect the growth rate of COVID-19, a study to comprehend transmission dynamics on human health

Coronavirus, Climate Change, and a Bit of Hope

Objective: many potential factors contribute to the outbreak of COVID-19.It aims to explore the effects of various meteorological factors on the incidence of COVID-19. Methods: Taking Hubei province of China as an example, where COVID-19 was first reported and there were the most cases, we collected 53 days of confirmed cases (total 67773 cases) and ten meteorological parameters up to March 10. Correlation analysis and linear regression were used to judge the relationship of meteorological factors and increment of COVID-19 confirmed cases. Results: Under 95% CI, the increment of confirmed cases in Hubei were correlated with four meteorological parameters of average pressure, average temperature, minimum temperature and average water vapor pressure (equivalent to absolute humidity).The average pressure was positively correlated with the increment (r=+0.358).The negative correlations included average temperature (r=-0.306), minimum temperature (r=-0.347), and average water vapor pressure (r=-0.326). The linear regression results show if minimum temperature increases by 1℃, the incremental confirmed cases in Hubei decreases by 72.470 units on average. Conclusion: Statistically, the incidence of COVID-19 was correlated with average pressure, average temperature, minimum temperature and average water vapor pressure. It is positively correlated with the average pressure and negatively correlated with the other three parameters. Compared with relative humidity, 2019-nCov is more sensitive to water vapor pressure. The reason why the epidemic situation in Hubei expanded rapidly is significantly related to the climate characteristics of low temperature and dryness of Hubei in winter.

Meteorological factors correlate with transmission of 2019-nCoV: Proof of incidence of novel coronavirus pneumonia in Hubei Province, China

Assessment of the risks posed by severe acute respiratory syndrome (SARS) coronavirus (SARS-CoV) on surfaces requires data on survival of this virus on environmental surfaces and on how survival is affected by environmental variables, such as air temperature (AT) and relative humidity (RH). The use of surrogate viruses has the potential to overcome the challenges of working with SARS-CoV and to increase the available data on coronavirus survival on surfaces. Two potential surrogates were evaluated in this study; transmissible gastroenteritis virus (TGEV) and mouse hepatitis virus (MHV) were used to determine effects of AT and RH on the survival of coronaviruses on stainless steel. At 4 degrees C, infectious virus persisted for as long as 28 days, and the lowest level of inactivation occurred at 20% RH. Inactivation was more rapid at 20 degrees C than at 4 degrees C at all humidity levels; the viruses persisted for 5 to 28 days, and the slowest inactivation occurred at low RH. Both viruses were inactivated more rapidly at 40 degrees C than at 20 degrees C. The relationship between inactivation and RH was not monotonic, and there was greater survival or a greater protective effect at low RH (20%) and high RH (80%) than at moderate RH (50%). There was also evidence of an interaction between AT and RH. The results show that when high numbers of viruses are deposited, TGEV and MHV may survive for days on surfaces at ATs and RHs typical of indoor environments. TGEV and MHV could serve as conservative surrogates for modeling exposure, the risk of transmission, and control measures for pathogenic enveloped viruses, such as SARS-CoV and influenza virus, on health care surfaces.

Effects of air temperature and relative humidity on coronavirus survival on surfaces.

The seasonality of influenza viruses and endemic human coronaviruses was tracked over an 8-year period to assess key epidemiologic reduction points in disease incidence for an urban area in the northeast United States. Patients admitted to a pediatric hospital with worsening respiratory symptoms were tested using a multiplex PCR assay from nasopharyngeal swabs. The additive seasonal effects of outdoor temperatures and indoor relative humidity (RH) were evaluated. The 8-year average peak activity of human coronaviruses occurred in the first week of January, when droplet and contact transmission was enabled by the low indoor RH of 20-30%. Previous studies have shown that an increase in RH to 50% has been associated with markedly reduced viability and transmission of influenza virus and animal coronaviruses. As disease incidence was reduced by 50% in early March, to 75% in early April, to greater than 99% at the end of April, a relationship was observed from colder temperatures in January with a low indoor RH to a gradual increase in outdoor temperatures in April with an indoor RH of 45-50%. As a lipid-bound, enveloped virus with similar size characteristics to endemic human coronaviruses, SARS-CoV-2 should be subject to the same dynamics of reduced viability and transmission with increased humidity. In addition to the major role of social distancing, the transition from lower to higher indoor RH with increasing outdoor temperatures could have an additive effect on the decrease in SARS-CoV-2 cases in May. Over the 8-year period of this study, human coronavirus activity was either zero or >99% reduction in the months of June through September, and the implication would be that SARS-Cov-2 may follow a similar pattern.

The Seasonal End of Human Coronavirus Hospital Admissions with Implications for SARS-CoV-2

Abstract The undefendable outbreak of novel coronavirus (SARS-COV-2) lead to a global health emergency due to its higher transmission rate and longer symptomatic duration, created a health surge in a short time. Since Nov 2019 the outbreak in China, the virus is spreading exponentially everywhere. The current study focuses on the relationship between environmental parameters and the growth rate of COVID-19. The statistical analysis suggests that the temperature changes retarded the growth rate and found that -6.28°C and +14.51°C temperature is the favorable range for COVID-19 growth. Gutenberg- Richter's relationship is used to estimate the mean daily rate of exceedance of confirmed cases concerning the change in temperature. Indeed, temperature is the most influential parameter that reduces the growth at the rate of 13-17 cases/day with a 1°C rise in temperature.

It is well-known that atmospheric pollution, first and foremost the particulate matter (PM), causes serious diseases in humans China’s metropolises and Italy’s Po Valley have in fact achieved a concerning degree of notoriety thanks to runaway air pollution problems The spread of viral respiratory diseases is facilitated in polluted environments, an example of which is the respiratory syncytial virus bronchiolitis In this opinion paper, we consider the possible relationship between air pollution, primarily airborne PM10–2 5, and the spread of the novel coronavirus in Northern Italy If it is true that the novel coronavirus remains active from some hours to several days on various surfaces, it is logical to postulate that the same can occur when it is adsorbed or absorbed by the atmospheric particulate matter, which may also help carry the virus into the human respiratory system As the Earth presents us with a very high bill to pay, governments and other authorities need to take prompt action to counter excessive pollution levels, both in Italy and in other countries

Novel Coronavirus: How Atmospheric Particulate Affects Our Environment and Health

Sub-continental Atmosphere and Inherent Immune System may have Impact on Novel Corona Virus' 2019 (nCovid-19) Prevalence in South East Asia

Scientists and doctors have observed for thousands of years that some diseases, such as polio and influenza, rise and fall with the seasons But why? Ongoing research in animals and humans suggests a variety of causes, including changes in the environment (like pH, temperature, and humidity) and even seasonal and daily changes to our own immune systems Figuring out those answers could one day make all the difference in minimizing the impact of infectious disease outbreaks—such as coronavirus disease 2019

How diseases rise and fall with the seasons—and what it could mean for coronavirus

UV (ultraviolet) light is an important factor should be considered to predict coronavirus epidemic growth pace. UV is different from weather temperature since UV is electromagnetic wavelength from 10 nm to 400 nm in size, shorter than of visible lights. For some people, UV light can lead to cancer from unprotected sun exposure, however, for tropical people, which have been used to live in such condition, have resisted from negative effect high UV index. Moreover, UV has the capability to inactivate virus. This conclusion has been discussed deeply with biological experts. Although UV light has the ability to inactivate viruses, it may be meaningless in areas with high air pollution where UV light turns into heat.

UV light influences covid-19 activity through big data: trade offs between northern subtropical, tropical, and southern subtropical countries

Recent literature has suggested that climate conditions have considerably significant influences on the transmission of coronavirus COVID-19. However, there is a lack of comprehensive study that investigates the relationships between multiple weather factors and the development of COVID-19 pandemic while excluding the impact of social factors. In this paper, we study the relationships between six main weather factors and the infection statistics of COVID-19 on 250 cities in Mainland China. Our correlation analysis using weather and infection statistics indicates that all the studied weather factors are correlated with the spread of COVID-19, where precipitation shows the strongest correlation. We also build a weather-aware predictive model that forecasts the number of infected cases should there be a second wave of the outbreak in Mainland China. Our predicted results show that cities located in different geographical areas are likely to be challenged with the second wave of COVID-19 at very different time periods and the severity of the outbreak varies to a large degree, in correspondence with the varying weather conditions.

The Weather Impacts the Outbreak of COVID-19 in Mainland China

Using a model developed for estimating solar inactivation of viruses of biodefense concerns, we calculated the expected inactivation of SARS‐CoV‐2 virus, cause of COVID‐19 pandemic, by artificial UVC and by solar ultraviolet radiation in several cities of the world during different times of the year. The UV sensitivity estimated here for SARS‐CoV‐2 is compared with those reported for other ssRNA viruses, including influenza A virus. The results indicate that SARS‐CoV‐2 aerosolized from infected patients and deposited on surfaces could remain infectious outdoors for considerable time during the winter in many temperate‐zone cities, with continued risk for re‐aerosolization and human infection. Conversely, the presented data indicate that SARS‐CoV‐2 should be inactivated relatively fast (faster than influenza A) during summer in many populous cities of the world, indicating that sunlight should have a role in the occurrence, spread rate, and duration of coronavirus pandemics.

Estimated Inactivation of Coronaviruses by Solar Radiation With Special Reference to COVID‐19

Preliminary evidence suggests that climate may modulate the transmission of SARS-CoV-2. Yet it remains unclear whether seasonal and geographic variations in climate can substantially alter the pandemic trajectory, given high susceptibility is a core driver. Here, we use a climate-dependent epidemic model to simulate the SARS-CoV-2 pandemic probing different scenarios based on known coronavirus biology. We find that while variations in weather may be important for endemic infections, during the pandemic stage of an emerging pathogen the climate drives only modest changes to pandemic size. A preliminary analysis of non-pharmaceutical control measures indicates that they may moderate the pandemic-climate interaction via susceptible depletion. Our findings suggest, without effective control measures, strong outbreaks are likely in more humid climates and summer weather will not substantially limit pandemic growth.

Susceptible supply limits the role of climate in the early SARS-CoV-2 pandemic

Environmental factors, including seasonal climatic variability, can strongly impact on spatio-temporal patterns of infectious disease outbreaks, but relationships between Covid-19 dynamics and climate remain controversial. We assessed the impact of temperature and humidity on the global patterns of Covid-19 early outbreak dynamics during January-March 2020. Here we show that Covid-19 growth rates peaked in temperate regions of the Northern Hemisphere with mean temperature of ~5 C, and specific humidity of 4-6 g/m3 during the outbreak period, while they were lower both in warmer/wetter and colder/dryer regions. Relationships between Covid-19 and climate were robust to the potential confounding effects of air pollution and socio-economic variables, including population size, density and health expenditure. The strong relationship between local climate and Covid-19 growth rates suggests the possibility of seasonal variation in the spatial pattern of outbreaks, with temperate regions of the Southern Hemisphere becoming at particular risk of severe outbreaks during the austral autumn-winter.

Climate affects global patterns of COVID-19 early outbreak dynamics

Since the World Health Organization has declared the current outbreak of the novel coronavirus (COVID-19) a global pandemic, some have been anticipating that the mitigation could happen in the summer like seasonal influenza, while medical solutions are still in a slow progress. Experimental studies have revealed a few evidences that coronavirus decayed quickly under the exposure of heat and humidity. This study aims to carry out an epidemiological investigation to establish the association between meteorological factors and COVID-19 in high risk areas of the United States (U.S.). We analyzed daily new confirmed cases of COVID-19 and seven meteorological measures in top 50 U.S. counties with the most accumulative confirmed cases from March 22, 2020 to April 22, 2020. Our analyses indicate that each meteorological factor and COVID-19 more likely have a nonlinear association rather than a linear association over the wide ranges of temperature, relative humidity, and precipitation observed. Average temperature, minimum relative humidity, and precipitation were better predictors to address the meteorological impact on COVID-19. By including all the three meteorological factors in the same model with their lagged effects up to 3 days, the overall impact of the average temperature on COVID-19 was found to peak at 68.45 °F and decrease at higher degrees, though the overall relative risk percentage (RR %) reduction did not become significantly negative up to 85 °F. There was a generally downward trend of RR % with the increase of minimum relative humidity; nonetheless, the trend reversed when the minimum relative humidity exceeded 91.42%. The overall RR % of COVID-19 climbed to the highest level of 232.07% (95% confidence interval = 199.77, 267.85) with 1.60 inches of precipitation, and then started to decrease. When precipitation exceeded 1.85 inches, its impact on COVID-19 became significantly negative. Our findings alert people to better have self-protection during the pandemic rather than expecting that the natural environment can curb coronavirus for human beings.

Meteorological impacts on the incidence of COVID-19 in the U.S.

As the number of confirmed cases of Coronavirus disease 2019 (COVID-19) continues to increase, there has been a rising concern regarding the effect of weather conditions, especially over the upcoming summer, on the transmission of this disease. In this study, we assess the transmission of COVID-19 under different weather conditions by investigating the propagation of infectious respiratory droplets. A comprehensive mathematical model is established to explore their evaporation, heat transfer and kinematics under different temperature, humidity and ventilation conditions. The transmitting pathway of COVID-19 through respiratory droplets is divided into short-range droplet contacts and long-range aerosol exposure. We show that the effect of weather conditions is not monotonic: low temperature and high humidity facilitate droplet contact transmission, while high temperature and low humidity promote the formation of aerosol particles and accumulation of particles with a diameter of 2.5 m or less (PM2.5). Our model suggests that the 6 ft of social distance recommended by the Center for Disease Control and Prevention (CDC) may be insufficient in certain environmental conditions, as the droplet spreading distance can be as long as 6 m (19.7 ft) in cold and humid weather. The results of this study suggest that the current pandemic may not ebb in the summer of the northern hemisphere without proper intervention, as there is an increasing chance of aerosol transmission. We also emphasize that the meticulous design of building ventilation systems is critical in containing both the droplet contact infections and aerosol exposures.

COVID-19: Effects of weather conditions on the propagation of respiratory droplets

Coronavirus disease 2019 (COVID19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARSCoV2), it was first identified in 2019 in Wuhan, China and has resulted in the 2019-20 coronavirus pandemic. As of March 1, 2020, 79,968 patients in China and 7169 outside of China had tested positive for COVID19 and a mortality rate of 3.6% has been observed amongst Chinese patients. Its primary mode of transmission is via respiratory droplets from coughs and sneezes. The virus can remain viable for up to three days on plastic and stainless steel or in aerosols for upto 3 hours and is relatively more stable than the known human coronaviruses. It is stable in faeces at room temperature for at least 1-2 days and can be stable in infected patients for up to 4 days. Heat at 56 degree Celsius kills the SARS coronavirus at around 10000 units per 15 minutes. Thus, temperature is an important factor in survival of COVID19 virus and this article focuses on understanding the relationship between temperature and COVID19 transmission from the data available between January-March 2020.

Effects of temperature on COVID-19 transmission

On February 1, 2020, China announced a novel coronavirus CoVID-19 outbreak to the public. CoVID-19 was classified as an epidemic by the World Health Organization (WHO). Although the disease was discovered and concentrated in Hubei Province, China, it was exported to all of the other Chinese provinces and spread globally. As of this writing, all plans have failed to contain the novel coronavirus disease, and it has continued to spread to the rest of the world. This study aimed to explore and interpret the effect of environmental and metrological variables on the spread of coronavirus disease in 30 provinces in China, as well as to investigate the impact of new China regulations and plans to mitigate further spread of infections. This article forecasts the size of the disease spreading based on time series forecasting. The growing size of CoVID-19 in China for the next 210 days is estimated by predicting the expected confirmed and recovered cases. The results revealed that weather conditions largely influence the spread of coronavirus in most of the Chinese provinces. This study has determined that increasing temperature and short-wave radiation would positively increase the number of confirmed cases, mortality rate, and recovered cases. The findings of this study agree with the results of our previous study.

The correlation between the spread of COVID-19 infections and weather variables in 30 Chinese provinces and the impact of Chinese government mitigation plans

The novel coronavirus (SARS-CoV-2/ 2019-nCoV) identified in Wuhan, China, in December 2019 has caused great damage to public health and economy worldwide with over 140,000 infected cases up to date. Previous research has suggested an involvement of meteorological conditions in the spread of droplet-mediated viral diseases, such as influenza. However, as for the recent novel coronavirus, few studies have discussed systematically about the role of daily weather in the epidemic transmission of the virus. Here, we examine the relationships of meteorological variables with the severity of the outbreak on a worldwide scale. The confirmed case counts, which indicates the severity of COVID-19 spread, and four meteorological variables, i.e., air temperature, relative humidity, wind speed, and visibility, were collected daily between January 20 and March 11 (52 days) for 430 cities and districts all over China, 21 cities/ provinces in Italy, 21 cities/ provinces in Japan, and 51 other countries around the world. Four different time delays of weather (on the day, 3 days ago, 7 days ago, and 14 days ago) as to the epidemic situation were taken for modeling and we finally chose the weather two weeks ago to model against the daily epidemic situation as its correlated with the outbreak best. Taken Chinese cities as a discovery dataset, it was suggested that temperature, wind speed, and relative humidity combined together could best predict the epidemic situation. The meteorological model could well predict the outbreak around the world with a high correlation (r2>0.6) with the real data. Using this model, we further predicted the possible epidemic situation in the future 12 days in several high-latitude cities with potential outbreak. This model could provide more information for government's future decisions on COVID-19 outbreak control.

Roles of meteorological conditions in COVID-19 transmission on a worldwide scale

As new cases of COVID-19 are being confirmed pressure is mounting to increase understanding of the factors underlying the spread the disease. Using data on local transmissions until the 23rd of March 2020, we develop an ensemble of 200 ecological niche models to project monthly variation in climate suitability for spread of SARS-CoV-2 throughout a typical climatological year. Although cases of COVID-19 are reported all over the world, most outbreaks display a pattern of clustering in relatively cool and dry areas. The predecessor SARS-CoV-1 was linked to similar climate conditions. Should the spread of SARS CoV-2 continue to follow current trends, asynchronous seasonal global outbreaks could be expected. According to the models, temperate warm and cold climates are more favorable to spread of the virus, whereas arid and tropical climates are less favorable. However, model uncertainties are still high across much of sub- Saharan Africa, Latin America and South East Asia. While models of epidemic spread utilize human demography and mobility as predictors, climate can also help constrain the virus. This is because the environment can mediate human-to-human transmission of SARS-CoV-2, and unsuitable climates can cause the virus to destabilize quickly, hence reducing its capacity to become epidemic.

Spread of SARS-CoV-2 Coronavirus likely to be constrained by climate

Several studies have confirmed the impact of weather conditions on the evolution of the Covid-19 pandemic. We wanted to verify this phenomenon in the city of Oran in Algeria, which experienced its first case of Covid19 on March 19, 2020. The data studied are the new Covid19 cases, the average, minimum and maximum temperatures, as well as the relative humidity rate. A first analysis of the data with a Spearman rank correlation test did not yield significant results. Taking into account the average incubation period to adjust the data made it possible, during a second analysis, to show that the minimum temperature is significantly correlated with the new cases of Covid19 in Oran. This study can help establish prevention policies against Covid19, especially during fall in temperatures in autumn and winter.

Impact of meteorological parameters on the Covid-19 incidence. The case of the city of Oran, Algeria.

We test the hypothesis of COVID-19 contagion being influenced by meteorological parameters such as temperature or humidity. We analysed data at high spatial resolution (regions in Italy and counties in the USA) and found that while at low resolution this might seem the case, at higher resolution no correlation is found. Our results are consistent with a poor outdoors transmission of the disease. However, a possible indirect correlation between good weather and a decrease in disease spread may occur, as people spend longer time outdoors.

Weather variables impact on COVID-19 incidence

Adaptation of species to new environments is governed by natural selection that discriminates among genetic variations and favors survival of the fittest. Here, we propose climate plays an important role in the evolution of SARS CoV-2 and the spread of COVID-19 all over the world which was previously not known. To understand the climatic factors responsible for shaping the molecular determinants of the novel coronavirus, genotyping SARS CoV-2 across different latitudes and Koppen’s climate is imperative. It seems this virus follows inverse latitudinal biodiversity gradient due to its preference towards Koppen’s temperate (C) and cold climate (D). Our molecular phylogenetic analysis revealed division of 176 SARS CoV-2 strains into two variant groups, G1 and G2, well defined by four mutations. Initially, SARS CoV-2 was restricted to a “humid-subtropical” (Cfa) climate of southeast China, which soon spread all over the world having C climate. Genomic information superimposed on global Koppen’s climate map elucidates that the gradation “humid-subtropical” (Cfa) and “marine-temperate” (Cfb) to “humid-continental” (Dfa-Dfb) climate drives the evolution of G1 into G2 variant group. It seems an early infection in Europe and USA is due to the dominance of C climate. Russia and North America were infected through linkage of C to D climate and South America from C to A climate. Our study elucidates viruses are sensitive to climate and combined genomic and climatic studies provide crucial information about the pathogenesis and natural spreading pathways during a pandemic which will enable us to take pre-emptive precautionary measures in such outbreaks. Graphical Abstract In Brief The authors elucidate adaptation of SARS CoV-2 to different climates by studying phylogenetics and the distribution of strains on Koppen’s climate map. Highlights SARS CoV-2 follows inverse latitudinal gradient. Phylogenetic network divides SARS CoV-2 strains into two variant groups, G1 and G2. G1 strains is restricted to Koppen’s “temperate” climate (mainly Cfa-Cfb). G2 strains has evolved from G1 to sustain in “humid-continental” (Dfa-Dfb) and “tropical-savannah” (Aw) climate.

Climatic-niche evolution of SARS CoV-2

The virus causing COVID-19 has spread rapidly worldwide and threatens millions of lives. It remains unknown if summer weather will reduce its continued spread, thereby alleviating strains on hospitals and providing time for vaccine development. Early insights from laboratory studies of related coronaviruses predicted that COVID-19 would decline at higher temperatures, humidity, and ultraviolet light. Using current, fine-scaled weather data and global reports of infection we developed a model that explained 36% of variation in early growth rates before intervention, with 17% based on weather or demography and 19% based on country-specific effects. We found that ultraviolet light was most strongly associated with lower COVID-19 growth rates. Projections suggest that, in the absence of intervention, COVID-19 will decrease temporarily during summer, rebound by autumn, and peak next winter. However, uncertainty remains high and the probability of a weekly doubling rate remained >20% throughout the summer in the absence of control. Consequently, aggressive policy interventions will likely be needed in spite of seasonal trends.

Seasonality and uncertainty in COVID-19 growth rates

Similar to other viruses, coronavirus infection triggers cellular stress responses in infected host cells. The close association of coronavirus replication with the endoplasmic reticulum (ER) results in the ER stress responses, which impose a challenge to the viruses. Viruses, in turn, have come up with various mechanisms to block or subvert these responses. One of the ER stress responses is inhibition of the global protein synthesis to reduce the amount of unfolded proteins inside the ER lumen. Viruses have evolved the capacity to overcome the protein translation shutoff to ensure viral protein production. Here, we review the strategies exploited by coronavirus to modulate cellular stress response pathways. The involvement of coronavirus-induced stress responses and translational control in viral pathogenesis will also be briefly discussed.

Regulation of Stress Responses and Translational Control by Coronavirus

The COVID-19 pandemic has led to six million confirmed cases by May 31, 2020. Impacts of regional weather and climate on epidemics have been investigated but need further study with new methods. We combined the number of monthly confirmed new cases and death with month, latitude, temperature, humidity, rainfall, and sunshine ultraviolet (UV) to explore the climate impact on epidemics in 116 countries and territories with at least 1000 confirmed cases. Correlation and regression analyses were performed with Stata. Humid subtropical climate regions had the most confirmed COVID-19 cases (24.4%). The case mortality in temperate marine regions was the highest (11.6%). Case-weighted means of the latitude, monthly maximum temperature, relative humidity, rainfall, and sunshine UV were 36.7 degrees, 20.5, 63%, 63mm, and 53.5, respectively. The case mortality was 7.44% in cold regions but only 4.68% in hot regions, 7.14% in rainy regions but only 3.86% in rainless regions, and 7.40% in cloudy regions but only 4.64% in sunny regions. Monthly confirmed cases increase as the temperature, rainfall, and sunshine UV rise in cold regions (r=0.34, 0.26, 0.26, respectively), but no correlation in hot regions. Every 1 increase in monthly maximum temperature leads to an increase in the natural logarithm of monthly confirmed new cases by 2.4% in cold regions. Monthly confirmed cases increase as the temperature, rainfall, and sunshine UV rise in arid regions (r=0.29, 0.28, 0.26, respectively), but no correlation in humid regions. Monthly confirmed new cases increase as the temperature and sunshine UV rise in rainy regions (r=0.30, 0.29), but no correlation in rainless regions. Monthly confirmed new deaths increase as the temperature and sunshine UV rise in cloudy regions (r=0.30, 0.30), but no correlation in sunny regions. It is wise to escape from an epicenter full of miasma to a hot sunny place in dry season without pollution. As peaking in the spring depends on the climate, the peak will go in the summer.

Impacts of regional climate on the COVID-19 pandemic

Abstract Background The relation between weather conditions, viral transmission and seasonal activity of respiratory viruses is not fully understood. Objectives To investigate the impact of outdoor weather in a temperate climate setting on the seasonal epidemiology of viruses causing respiratory tract infections, particularly influenza A (IFA). Study design In total, 20,062 clinical nasopharyngeal swab samples referred for detection of respiratory pathogens using a multiplex PCR panel, between October 2010 and July 2013, were included. Results of PCR detection were compared with local meteorological data for the same period. Results Low temperature and vapor pressure (VP) were associated with weekly incidence of IFA, respiratory syncytial virus, metapneumovirus, bocavirus and adenovirus but no association with relative humidity was found. The incidence of human rhinovirus and enterovirus was independent of temperature. During seasonal IFA outbreaks, the weekly drop of average temperature (compared with the week before) was strongly associated with the IFA incidence recorded the following week. Conclusion A sudden drop in outdoor temperature might activate the annual influenza epidemic in a temperate climate by facilitating aerosol spread in dry air. These conditions also seem to affect the incidence of other respiratory pathogens but not human rhino- or enterovirus, suggesting that routes of infection other than aerosol may be relevant for these agents.

A four year seasonal survey of the relationship between outdoor climate and epidemiology of viral respiratory tract infections in a temperate climate

The present study examines the impact of weather indicators on the COVID-19 outbreak in the majorly affected states of India. In this study, we hypothesize that the weather indicators could significantly influence the impact of the corona virus. The Kendall and Spearman rank correlation tests were chosen to conduct the statistical analysis. In this regard, we compiled a daily dataset including confirmed case counts, Recovered case counts, Deceased cases, Average Temperature, Maximum Relative Humidity, Maximum Wind Speed for six most affected states of India during the period of March 25, 2020 to April 24, 2020. We investigated that the average Humidity and Average Temperature seven days ago play a significant role in the recovery of coronavirus cases. The rise in average temperature will improve the recovery rate in the days to come. The cities with very high humidity levels or dry weather conditions have high probabilities of recovery from COVID-19. The findings of this research will help the policymakers to identify risky geographic areas and enforce timely preventive measures.

Impact of weather indicators on the COVID-19 outbreak: A multi-state study in India

The 2020 coronavirus pandemic is developing at different paces throughout the world. Some areas, like the Caribbean Basin, have yet to see the virus strike at full force. When it does, there is reasonable evidence to suggest the consequent COVID-19 outbreaks will overwhelm healthcare systems and economies. This is particularly concerning in the Caribbean as pandemics can have disproportionately higher mortality impacts on lower and middle-income countries. Preliminary observations from our team and others suggest that temperature and climatological factors could influence the spread of this novel coronavirus, making spatiotemporal predictions of its infectiousness possible. This review studies geographic and time-based distribution of known respiratory viruses in the Caribbean Basin in an attempt to foresee how the pandemic will develop in this region. This review is meant to aid in planning short- and long-term interventions to manage outbreaks at the international, national, and subnational levels in the region.

Weathering the pandemic: How the Caribbean Basin can use viral and environmental patterns to predict, prepare, and respond to COVID-19

Using a model developed for estimating solar inactivation of viruses of biodefense concerns, we calculated the expected inactivation of SARS-CoV-2 virus, cause of COVID-19 pandemic, by artificial UVC and by solar ultraviolet radiation in several cities of the world during different times of the year. The UV sensitivity estimated here for SARS-CoV-2 is compared with those reported for other ssRNA viruses, including influenza A virus. The results indicate that SARS-CoV-2 aerosolized from infected patients and deposited on surfaces could remain infectious outdoors for considerable time during the winter in many temperate-zone cities, with continued risk for re-aerosolization and human infection. Conversely, the presented data indicate that SARS-CoV-2 should be inactivated relatively fast (faster than influenza A) during summer in many populous cities of the world, indicating that sunlight should have a role in the occurrence, spread rate, and duration of coronavirus pandemics.

Estimated Inactivation of Coronaviruses by Solar Radiation With Special Reference to COVID-19

Using a model developed for estimating solar inactivation of viruses of biodefense concerns, we calculated the expected inactivation of SARS-CoV-2 virus, cause of COVID-19 pandemic, by artificial UVC and by solar ultraviolet radiation in several cities of the world during different times of the year. The UV sensitivity estimated here for SARS-CoV-2 is compared with those reported for other ssRNA viruses, including influenza A virus. The results indicate that SARS-CoV-2 aerosolized from infected patients and deposited on surfaces could remain infectious outdoors for considerable time during the winter in many temperate-zone cities, with continued risk for re-aerosolization and human infection. Conversely, the presented data indicate that SARS-CoV-2 should be inactivated relatively fast (faster than influenza A) during summer in many populous cities of the world, indicating that sunlight should have a role in the occurrence, spread rate and duration of coronavirus pandemics.

Results from two studies involving challenge with respiratory syncytial viruses showed that volunteers who developed colds were more sensitive to a visually distracting pattern presented prior to virus challenge than were volunteers who did not get a cold. Volunteers with sub-clinical infections reported more illusions after virus challenge than they had done before, whereas uninfected volunteers and those with colds tended to report fewer illusions on the second test. These effects did not occur when volunteers were challenged with either a coronavirus or rhinovirus. Overall, the results confirm that behavioural measures may be related to susceptibility to subsequent illness, and that viral infections may influence visual perception. They also show that the effects vary according to the nature of the infecting agent, which agrees with results from studies looking at other aspects of behaviour.

The common cold, pattern sensitivity and contrast sensitivity.

Coronavirus and Malta: weathering the storm

Abstract Background Our understanding of climate factors and their links to the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) outbreaks is incomplete. This study aimed to estimate the monthly incidence of MERS-CoV cases and to investigate their correlation to climate factors. Methods The study used aggregated monthly MERS-CoV cases that reported to the Saudi Center for Disease Prevention and Control from the Riyadh Region between November 1, 2012 and December 31, 2018. Data on the meteorological situation throughout the study period was calculated based on Google reports on the Riyadh Region (24.7136°N, 46.6753°E). The Poisson regression was used to estimate the incidence rate ratio (IRR) and its 95% confidence intervals (CI) for each climate factor. Results A total of 712 MERS-CoV cases were included in the analysis (mean age 54.2±9.9 years), and more than half (404) (56.1%) MERS-CoV cases were diagnosed during a five-month period from April to August. The highest peak timing positioned in August 2015, followed by April 2014, June 2017, March 2015, and June 2016. High temperatures (IRR=1.054, 95% CI: 1.043–1.065) and a high ultraviolet index (IRR=1.401, 95% CI: 1.331–1.475) were correlated with a higher incidence of MERS-CoV cases. However, low relative humidity (IRR=0.956, 95% CI: 0.948–0.964) and low wind speed (IRR=0.945, 95% CI: 0.912–0.979) were correlated with a lower incidence of MERS-CoV cases. Conclusion The novel coronavirus, MERS-CoV, is influenced by climate conditions with increasing incidence between April and August. High temperature, high ultraviolet index, low wind speed, and low relative humidity are contributors to increased MERS-CoV cases. The climate factors must be evaluated in hospitals and community settings and integrated into guidelines to serve as source of control measures to prevent and eliminate the risk of infection.

Climate factors and incidence of Middle East respiratory syndrome coronavirus

Twenty-four adult volunteers were inoculated with nasal drops containing a coronavirus of 229E serotype to determine the differences in the clinical and physiological reactions which occur between clinically infected, sub-clinically infected and non-infected individuals. Thirteen volunteers were clinically infected, 8 had sub-clinical infections and 3 were uninfected. Nasal airway resistance and the temperature of the nasal mucosa increased in all infected subjects both with and without symptoms: the core temperature increased also but to a lesser extent. Mucosal blood flow and nasal secretion increased only in those with symptoms. The albumin content of the nasal secretion increased in the clinically infected, suggesting that it was derived, partially at least, from the circulation. The nasal cycle of variation in airway resistance between the two sides of the nose was observed in all three groups but increased only in those clinically infected.

Changes in human nasal mucosa during experimental coronavirus common colds.

The main route of transmission of SARS CoV infection is presumed to be respiratory droplets. However the virus is also detectable in other body fluids and excreta. The stability of the virus at different temperatures and relative humidity on smooth surfaces were studied. The dried virus on smooth surfaces retained its viability for over 5 days at temperatures of 22–25°C and relative humidity of 40–50%, that is, typical air-conditioned environments. However, virus viability was rapidly lost (>3 log(10)) at higher temperatures and higher relative humidity (e.g., 38°C, and relative humidity of >95%). The better stability of SARS coronavirus at low temperature and low humidity environment may facilitate its transmission in community in subtropical area (such as Hong Kong) during the spring and in air-conditioned environments. It may also explain why some Asian countries in tropical area (such as Malaysia, Indonesia or Thailand) with high temperature and high relative humidity environment did not have major community outbreaks of SARS.

The Effects of Temperature and Relative Humidity on the Viability of the SARS Coronavirus

OBJECTIVE The causal agent for SARS is considered as a novel coronavirus that has never been described both in human and animals previously. The stability of SARS coronavirus in human specimens and in environments was studied. METHODS Using a SARS coronavirus strain CoV-P9, which was isolated from pharyngeal swab of a probable SARS case in Beijing, its stability in mimic human specimens and in mimic environment including surfaces of commonly used materials or in household conditions, as well as its resistance to temperature and UV irradiation were analyzed. A total of 10(6) TCID50 viruses were placed in each tested condition, and changes of the viral infectivity in samples after treatments were measured by evaluating cytopathic effect (CPE) in cell line Vero-E6 at 48 h after infection. RESULTS The results showed that SARS coronavirus in the testing condition could survive in serum, 1:20 diluted sputum and feces for at least 96 h, whereas it could remain alive in urine for at least 72 h with a low level of infectivity. The survival abilities on the surfaces of eight different materials and in water were quite comparable, revealing reduction of infectivity after 72 to 96 h exposure. Viruses stayed stable at 4 degrees C, at room temperature (20 degrees C) and at 37 degrees C for at least 2 h without remarkable change in the infectious ability in cells, but were converted to be non-infectious after 90-, 60- and 30-min exposure at 56 degrees C, at 67 degrees C and at 75 degrees C, respectively. Irradiation of UV for 60 min on the virus in culture medium resulted in the destruction of viral infectivity at an undetectable level. CONCLUSION The survival ability of SARS coronavirus in human specimens and in environments seems to be relatively strong. Heating and UV irradiation can efficiently eliminate the viral infectivity.

Stability of SARS coronavirus in human specimens and environment and its sensitivity to heating and UV irradiation.

It is shown that the evaporation rate of a liquid sample containing the culture of coronavirus affects its survival on a substrate. Possible mechanisms of such influence can be due to the appearance of large, about 140 bar, non comprehensive capillary pressures and the associated dynamic forces during the movement of the evaporation front in a sample with the virus. A simulation of isothermal evaporation of a thin liquid sample based on the Stefan problem was performed. The comparison of simulation data and recent experiments on the coronavirus survival on various surfaces showed that the rate of isothermal evaporation of aqueous samples, which is higher for heat-conducting materials, correlates well with the lifetime of the coronavirus on these surfaces.

Isothermal evaporation rate of deposited liquid aerosols and the SARS-CoV-2 coronavirus survival

The rapid global spread of the novel, pathogenic, SARS-CoV-2 causing the severe acute respiratory disease COVID-19, becomes a major health problem worldwide and pose the need for international predictive programs. Given the lack of both specific drugs and an efficient preventive vaccine, the expectation that SARS-CoV-2 transmission rate might decrease in temperate regions during summer, dominated the social scene. Here, we attempted a prediction of the worldwide spread of the infections based on climatic data, expressed by 19 bioclimatic variables. The calculated probability maps shown that potential areas of infection follow a shift from the Tropical to Temperate and Mediterranean Bioclimatic regions, and back to the Tropics again. Maps show an increased probability of infections in Europe, followed by an expansion covering areas of the Middle East and Northern Africa, as well as Eastern coastal areas of North America, South-Eastern coastal areas of Latin America and two areas of Southern Australia, and later return to areas of Southeastern Asia, in a manner similar to that of influenza strains (H3N2). Our approach may therefore be of value for the worldwide spread of SARS-CoV-2, suggesting an optimistic scenario of asynchronous seasonal global outbreaks, like other viral respiratory diseases. Consequently, we suggest the incorporation of a climatic impact in the design and implementation of public health policies. Maps of our model are available (constantly updated up to the saturation of the model) at: https://navaak.shinyapps.io/CVRisk/.

Climatic influences on the worldwide spread of SARS-CoV-2

Temperature and relative humidity are major factors determining virus inactivation in the environment. This article reviews inactivation data of coronaviruses on surfaces and in liquids from published studies and develops secondary models to predict coronaviruses inactivation as a function of temperature and relative humidity. A total of 102 D-values (time to obtain a log10 reduction of virus infectivity), including values for SARS-CoV-2, were collected from 26 published studies. The values obtained from the different coronaviruses and studies were found to be generally consistent. Five different models were fitted to the global dataset of D-values. The most appropriate model considered temperature and relative humidity. A spreadsheet predicting the inactivation of coronaviruses and the associated uncertainty is presented and can be used to predict virus inactivation for untested temperatures, time points or new coronavirus strains.

Modelling the thermal inactivation of viruses from the Coronaviridae family in suspensions or on surfaces with various relative humidities.

The Coronaviridae family, an enveloped RNA virus family, and, more particularly, human coronaviruses (HCoV), were historically known to be responsible for a large portion of common colds and other upper respiratory tract infections. HCoV are now known to be involved in more serious respiratory diseases, i.e. bronchitis, bronchiolitis or pneumonia, especially in young children and neonates, elderly people and immunosuppressed patients. They have also been involved in nosocomial viral infections. In 2002–2003, the outbreak of severe acute respiratory syndrome (SARS), due to a newly discovered coronavirus, the SARS-associated coronavirus (SARS-CoV); led to a new awareness of the medical importance of the Coronaviridae family. This pathogen, responsible for an emerging disease in humans, with high risk of fatal outcome; underline the pressing need for new approaches to the management of the infection, and primarily to its prevention. Another interesting feature of coronaviruses is their potential environmental resistance, despite the accepted fragility of enveloped viruses. Indeed, several studies have described the ability of HCoVs (i.e. HCoV 229E, HCoV OC43 (also known as betacoronavirus 1), NL63, HKU1 or SARS-CoV) to survive in different environmental conditions (e.g. temperature and humidity), on different supports found in hospital settings such as aluminum, sterile sponges or latex surgical gloves or in biological fluids. Finally, taking into account the persisting lack of specific antiviral treatments (there is, in fact, no specific treatment available to fight coronaviruses infections), the Coronaviridae specificities (i.e. pathogenicity, potential environmental resistance) make them a challenging model for the development of efficient means of prevention, as an adapted antisepsis-disinfection, to prevent the environmental spread of such infective agents. This review will summarize current knowledge on the capacity of human coronaviruses to survive in the environment and the efficacy of well-known antiseptic-disinfectants against them, with particular focus on the development of new methodologies to evaluate the activity of new antiseptic-disinfectants on viruses.

Human Coronaviruses: Insights into Environmental Resistance and Its Influence on the Development of New Antiseptic Strategies

The 2020 coronavirus pandemic is developing at different paces throughout the world. Some areas, like the Caribbean Basin, have yet to see the virus strike at full force. When it does, there is reasonable evidence to suggest the consequent COVID‐19 outbreaks will overwhelm healthcare systems and economies. This is particularly concerning in the Caribbean as pandemics can have disproportionately higher mortality impacts on lower and middle income countries. Preliminary observations from our team and others suggest that temperature and climatological factors could influence the spread of this novel coronavirus, making spatiotemporal predictions of its infectiousness possible. This review studies geographic and time‐based distribution of known respiratory viruses in the Caribbean Basin in an attempt to foresee how the pandemic will develop in this region. This review is meant to aid in planning short‐ and long‐term interventions to manage outbreaks at the international, national and sub‐national levels in the region. This article is protected by copyright. All rights reserved.

Weathering the pandemic: How the Caribbean Basin can use viral and environmental patterns to predict, prepare and respond to COVID‐19

The correlation between the spread of COVID-19 infections and weather variables in 30 Chinese provinces and the impact of Chinese government mitigation plans.

Recently, anovel coronavirus virus disease (COVID-19) has become a serious concern for global public health hazards. Infectious disease outbreaks such as COVID-19can also significantly affect the sustainable development of urban areas. Several factors such as population density and climatology parameters could potentially affect the spread of the COVID-19. In this study, a combination of the virus optimization algorithm (VOA) and adaptive network-based fuzzy inference system (ANFIS) to investigate the effects of various climate-related factors and population density on the spread of the COVID-19. For this purpose, data on the climate-related factors and the confirmed infected cases by the COVID-19across the U.S counties was used.The results show that the variable defined for the population density had the most significant impact on the performance of the developed models, which is an indication of the importance social distancing in reducing the infection rate and spread rate of the COVID-19. Among the climatology parameters, an increase in the maximum temperature was found to reduce the infection rate. Average temperature, minimum temperature, precipitation, and average wind speed were not found to significantly affect the spread of the COVID-19 while an increase in the relative humidity was found to slightly increase the infection rate. The findings of this research show that it could be expected to have reduced infection rate over the summer season. However, it should be noted that the models developed in this study were based on limited one-month data. Future investigation can benefit from using more comprehensive data covering a wider range for the input variables.

Determinants of the infection rate of the COVID-19 in the U.S. using ANFIS and virus optimization algorithm (VOA)

The COVID-19 pandemic has outspread obstreperously in India. As of June 04, 2020, more than 2 lakh cases have been confirmed with a death rate of 2.81%. It has been noticed that, out of each 1000 tests, 53 result positively infected. In order to investigate the impact of weather conditions on daily transmission occurring in India, daily data of Maximum (TMax), Minimum (TMin), Mean (TMean) and Dew Point Temperature (TDew), Diurnal Temperature range (TRange), Average Relative Humidity, Range in Relative Humidity, and Wind Speed (WS) over 9 most affected cities are analysed in several time frames: weather of that day, 7, 10, 12, 14, 16 days before transmission. Spearman rank correlation (r) shows significant but low correlation with most of the weather parameters, however, comparatively better association exists on 14 days lag. Diurnal range in Temperature and Relative Humidity shows non-significant correlation. Analysis shows, COVID-19 cases likely to be increased with increasing air temperature, however role of humidity is not clear. Among weather parameters, Minimum Temperature was relatively better correlate than other. 80% of the total confirmed cases were registered when TMax, TMean, TMin, TRange, TDew, and WS on 12-16 days ago vary within a range of 33.6-41.3 deg C, 29.8-36.5 deg C, 24.8-30.4 deg C, 7.5-15.2 deg C, 18.7-23.6 deg C, and 4.2-5.75 m/s respectively, hence, it gives an idea of susceptible weather conditions for such transmission in India. Using Support Vector Machine based regression, the daily cases are profoundly estimated with more than 80% accuracy, which indicate that coronavirus transmission cannot be well linearly correlated with any single weather parameters, rather multivariate non-linear approach must be employed. Accounting lag of 12-16 days, the association found to be excellent, thus depict that there is an incubation period of 12-16 days for coronavirus transmission in Indian scenario.

Impact of Daily Weather on COVID-19 outbreak in India

BACKGROUND: Previous reports have suggested that transmission of SARS-CoV-2 is reduced by higher temperatures and higher humidity. We analyzed case-data from the United States to investigate effects of temperature, precipitation, and UV Light on community transmission of SARS-CoV-2. METHODS: Daily reported cases of SARS-CoV-2 across the United States from 01/22/2020 to 04/03/2020 were analyzed. We used negative binomial regression modelling to investigate whether daily maximum temperature, precipitation, UV Index and the incidence 5 days later were related. We performed sensitivity analyses at 3 days, 7 days and 9 days to assess transmission lags. RESULTS: A maximum temperature greater than 52°F on a given day was associated with a lower rate of new cases at 5 days[IRR: 0.85(0.76,0.96)p=0.009]. Among observations with daily temperatures below 52°F, there was a significant inverse association between the maximum daily temperature and the rate of cases at 5 days [IRR 0.98(0.97,0.99)p=0.001]. The rate of new cases was predicted to be lower for theoretical states that maintained a stable maximum daily temperature above 52°F with a predicted 23-fewer cases per-million per-day by 25 days of the epidemic. A 1-unit higher UV index was associated with a lower rate at 5 days [IRR 0.97(0.95,0.99)p=0.004]. Precipitation was not associated with a greater rate of cases at 5 days [IRR 0.98(0.89,1.08)p=0.65]. CONCLUSION: The incidence of disease declines with increasing temperature up until 52°F and is lower at warmer versus cooler temperatures. However, the association between temperature and transmission is small and transmission is likely to remain high at warmer temperatures.

Maximum Daily Temperature, Precipitation, Ultra-Violet Light and Rates of Transmission of SARS-Cov-2 in the United States

Quantifying the role of temperature and humidity on the transmission of SARS-CoV-2 has been confounded by a lack of controlled experiments, the sudden rise in detection rates, and changing weather patterns. In this paper we focus our analysis on data from Colombia, which presents unique economic, demographic and geological characteristics that favor the study of temperature and humidity upon SARS-CoV-2 transmission: the weather varies dramatically across five natural regions (from the Caribbean coast and the Amazon rainforest to the Andean mountains), there are no pronounced seasons, there is a central port of entry, the use of public transportation dominates inter- and intracity travel, and indoor climate control is rare. While only controlled experiments can precisely quantify the role of temperature and humidity upon SARS-CoV-2 transmission, we observe significant attenuation of transmission in climates with sustained daily maximum temperatures above 30 degrees Celsius and simultaneous mean relative humidity below 78%. We hypothesize that temperature and relative humidity comodulate the infectivity of SARS-CoV-2 within respiratory droplets.

The transmission of SARS-CoV-2 is likely comodulated by temperature and by relative humidity

The evolution of new and reemerging historic virulent strains of respiratory viruses from animal reservoirs is a significant threat to human health. Inefficient human-to-human transmission of zoonotic strains may initially limit the spread of transmission, but an infection may be contracted by touching contaminated surfaces. Enveloped viruses are often susceptible to environmental stresses, but the human coronaviruses responsible for severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) have recently caused increasing concern of contact transmission during outbreaks. We report here that pathogenic human coronavirus 229E remained infectious in a human lung cell culture model following at least 5 days of persistence on a range of common nonbiocidal surface materials, including polytetrafluoroethylene (Teflon; PTFE), polyvinyl chloride (PVC), ceramic tiles, glass, silicone rubber, and stainless steel. We have shown previously that noroviruses are destroyed on copper alloy surfaces. In this new study, human coronavirus 229E was rapidly inactivated on a range of copper alloys (within a few minutes for simulated fingertip contamination) and Cu/Zn brasses were very effective at lower copper concentration. Exposure to copper destroyed the viral genomes and irreversibly affected virus morphology, including disintegration of envelope and dispersal of surface spikes. Cu(I) and Cu(II) moieties were responsible for the inactivation, which was enhanced by reactive oxygen species generation on alloy surfaces, resulting in even faster inactivation than was seen with nonenveloped viruses on copper. Consequently, copper alloy surfaces could be employed in communal areas and at any mass gatherings to help reduce transmission of respiratory viruses from contaminated surfaces and protect the public health.

Human Coronavirus 229E Remains Infectious on Common Touch Surface Materials

Coronaviruses (CoV) are a large family of viruses causing a spectrum of disease ranging from the common cold to more severe diseases as Middle East Respiratory Syndrome (MERS-CoV) and Severe Acute Respiratory Syndrome (SARS-CoV). The recent outbreak of coronavirus disease 2019 (COVID-19) has become a public health emergency worldwide. SARS-CoV-2, the virus responsible for COVID-19, is spread by human-to-human transmission via droplets or direct contact. However, since SARS-CoV-2 (as well as other coronaviruses) has been found in the fecal samples and anal swabs of some patients, the possibility of fecal-oral (including waterborne) transmission need to be investigated and clarified. This scoping review was conducted to summarize research data on CoV in water environments. A literature survey was conducted using the electronic databases PubMed, EMBASE, and Web Science Core Collection. This comprehensive research yielded more than 3000 records, but only 12 met the criteria and were included and discussed in this review. In detail, the review captured relevant studies investigating three main areas: 1) CoV persistence/survival in waters; 2) CoV occurrence in water environments; 3) methods for recovery of CoV from waters. The data available suggest that: i) CoV seems to have a low stability in the environment and is very sensitive to oxidants, like chlorine; ii) CoV appears to be inactivated significantly faster in water than non-enveloped human enteric viruses with known waterborne transmission; iii) temperature is an important factor influencing viral survival (the titer of infectious virus declines more rapidly at 23°C-25 °C than at 4 °C); iv) there is no current evidence that human coronaviruses are present in surface or ground waters or are transmitted through contaminated drinking-water; v) further research is needed to adapt to enveloped viruses the methods commonly used for sampling and concentration of enteric, non enveloped viruses from water environments. The evidence-based knowledge reported in this paper is useful to support risk analysis processes within the drinking and wastewater chain (i.e., water and sanitation safety planning) to protect human health from exposure to coronavirus through water.

Coronavirus in water environments: Occurrence, persistence and concentration methods - A scoping review

Due to the close relationship between the incidence of infectious diseases by epidemics and environmental conditions, this research explores the temperature, evaporation, precipitation and regional climate effects on the local transmission of coronavirus SARS-CoV-2 inside 31 states and capital of Mexico since February 29 (national onset) to March 31, 2020. Statistical analysis was conducted to explore the association between the daily local COVID-19 confirmed positive cases (LCPC) and both climate characteristics and the daily weather reported by the regional meteorological stations. In this work, the local transmission ratio (LTR) was calculated with the regional LCPC divided by the number of the effective contagion days since regional onset in each state. The results showed a negative association between temperature (mean, max and min) and climate classification with both LCPC and LTR variables. The precipitation associated positively with LCPC and LTR. The associations between the climate classification with LCPC and LTR are statistically significant. The tropical climate (mean temperature around 25.95â¯°C and mean precipitation around 8.74â¯mm) delayed the regional onset. However, the regional onset in dry climates emerged earlier as consequence of the lower temperatures and higher precipitations (20.57â¯°C and 20.87â¯mm respectively) than the observed in the tropical climate. The fastest regional onsets were observed in tempered climates in states where the lowest temperatures and lowest precipitations were registered (19.65â¯°C and 8.48â¯mm respectively). Meteorological factors influenced the trend on the regional outbreaks in Mexican's states likely by the host predisposition and susceptibility during the cold winter season. In Mexico, the climate characteristics played a crucial role on the local infection during the phase 1 being the tempered regions (as Michoacán, Jalisco, Puebla, etc.) more vulnerable than the dry (as Chihuahua, Durango or Zacatecas, etc.) or tropical areas (as Colima, Campeche, Morelos etc.).

The temperature and regional climate effects on communitarian COVID-19 contagion in Mexico throughout phase 1

This paper investigates whether the Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) pandemic could have been favored by specific weather conditions and other factors. It is found that the 2020 winter weather in the region of Wuhan (Hubei, Central China)-where the virus first broke out in December and spread widely from January to February 2020-was strikingly similar to that of the Northern Italian provinces of Milan, Brescia and Bergamo, where the pandemic broke out from February to March. The statistical analysis was extended to cover the United States of America, which overtook Italy and China as the country with the highest number of confirmed COronaVIrus Disease 19 (COVID-19) cases, and then to the entire world. The found correlation patterns suggest that the COVID-19 lethality significantly worsens (4 times on average) under weather temperatures between 4 ∘ C and 12 ∘ C and relative humidity between 60% and 80%. Possible co-factors such as median population age and air pollution were also investigated suggesting an important influence of the former but not of the latter, at least, on a synoptic scale. Based on these results, specific isotherm world maps were generated to locate, month by month, the world regions that share similar temperature ranges. From February to March, the 4-12 ∘ C isotherm zone extended mostly from Central China toward Iran, Turkey, West-Mediterranean Europe (Italy, Spain and France) up to the United State of America, optimally coinciding with the geographic regions most affected by the pandemic from February to March. It is predicted that in the spring, as the weather gets warm, the pandemic will likely worsen in northern regions (United Kingdom, Germany, East Europe, Russia and North America) while the situation will likely improve in the southern regions (Italy and Spain). However, in autumn, the pandemic could come back and affect the same regions again. The Tropical Zone and the entire Southern Hemisphere, but in restricted colder southern regions, could avoid a strong pandemic because of the sufficiently warm weather during the entire year and because of the lower median age of their population. Google-Earth-Pro interactive-maps covering the entire world are provided as supplementary files.

Distribution of the SARS-CoV-2 Pandemic and Its Monthly Forecast Based on Seasonal Climate Patterns

Previous research has identified a relationship between climate and occurrence of SARS‐CoV and MERS‐CoV cases, information that can be used to reduce the risk of infection. Using COVID‐19 notification and postcode data from New South Wales, Australia during the exponential phase of the epidemic in 2020, we used time series analysis to investigate the relationship between 749 cases of locally acquired COVID‐19 and daily rainfall, 9 a.m. and 3 p.m. temperature, and 9 a.m. and 3 p.m. relative humidity. Lower 9 a.m. relative humidity (but not rainfall or temperature) was associated with increased case occurrence; a reduction in relative humidity of 1% was predicted to be associated with an increase of COVID‐19 cases by 6.11%. During periods of low relative humidity, the public health system should anticipate an increased number of COVID‐19 cases.

The role of climate during the COVID‐19 epidemic in New South Wales, Australia

Preliminary evidence suggests that climate may modulate the transmission of SARS-CoV-2. Yet it remains unclear whether seasonal and geographic variations in climate can substantially alter the pandemic trajectory, given high susceptibility is a core driver. Here, we use a climate-dependent epidemic model to simulate the SARS-CoV-2 pandemic probing different scenarios of climate-dependence based on known coronavirus biology. We find that while variations in humidity may be important for endemic infections, during the pandemic stage of an emerging pathogen such as SARS-CoV-2 climate may drive only modest changes to pandemic size and duration. Our results suggest that, in the absence of effective control measures, significant cases in the coming months are likely to occur in more humid (warmer) climates, irrespective of the climate-dependence of transmission and that summer temperatures will not substantially limit pandemic growth.

Susceptible supply limits the role of climate in the COVID-19 pandemic

A novel coronavirus (SARS-CoV-2) first detected in Wuhan, China, has spread rapidly since December 2019, causing more than 100,000 confirmed infections and 4000 fatalities (as of 10 March 2020). The outbreak has been declared a pandemic by the WHO on Mar 11, 2020. 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 parameterise 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.

Potential impact of seasonal forcing on a SARS-CoV-2 pandemic.

Potential impact of seasonal forcing on a SARS-CoV-2 pandemic

The COVID-19 disease, a respiratory disease transmitted by a new betacoronavirus SARS-CoV-2. As for other viral respiratory agents, SARS-CoV-2 spreads by person to person through respiratory droplets and direct contact and potentially by indirect contact through fomites. The goal of the current study is to evaluate whether the increase of temperature can influence the environmental endurance of SARS-CoV-2.We tested SARS-CoV-2 environmental stability in parallel at room temperature (RT, 20-25 Celsius degrees) and at average maximum temperature of June (JT) estimated at 28 Celsius degrees in Italy. The virus inoculated on plastic surface was harvested at predefined time-points and tested to evaluate viral titres on Vero cells by TCID50. Our results confirm that fomite transmission of the emerging SARS-CoV2 is possible, since the virus remains viable on surfaces up to 84 hours at both RT and JT. Moreover, a remarkable difference between the two temperatures exists, suggesting that virus vitality can be influenced by the environmental temperature. Our results support the hypothesis that in the hot season the increase of temperature could influence the environmental endurance of SARS-CoV2 and reduce Covid-19 transmission probability.

SARS-CoV-2 infection: the environmental endurance of the virus can be influenced by the increase of temperature

The present work describes spreading of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) at the tropical and temperate zones which are explained based on insolation energy, Particulate Matter (PM(2.5)), latitude, temperature, humidity, Population Density (PD), Human Development Index (HDI) and Global Health Security Index (GHSI) parameters. In order to analyze the spreading of SARS-CoV-2 by statistical data based on the confirmed positive cases which are collected between December 31, 2019 to April 25, 2020. The present analysis reveals that the outbreak of SARS-CoV-2 in the major countries lie on the Equator is 78,509 cases, the countries lie on the Tropic of Cancer is 62,930 cases (excluding China) and the countries lie on the Tropic of Capricorn is 22,842 cases. The tropical countries, which comes between the Tropic of Cancer and Tropic of Capricorn is reported to be 1,77,877 cases. The temperate zone countries, which are above and below the tropical countries are reported to be 25, 66,171 cases so, the pandemic analysis describes the correlation between latitude, temperate zones, PM(2.5) and local environmental factors. Hence, the temperature plays a pivotal role in the spreading of coronavirus at below 20 °C. The spreading of SARS-CoV-2 cases in Northern and Southern Hemispheres has inverse order against absorption of insolated energy. In temperate zone countries, the concentration of PM(2.5) at below 20 μg/m(3) has higher spreading rate of SARS-CoV-2 cases. The effect of insolation energy and PM(2.5), it is confirmed that the spreading of SARS-CoV-2 is explained by dumb-bell model and solid/liquid interface formation mechanism. The present meta-analysis also focuses on the impact of GHSI, HDI, PD and PM(2.5) on spreading of SARS-CoV-2 cases.

The effect of latitude and PM(2.5) on spreading of SARS-CoV-2 in tropical and temperate zone countries()

Cell surface receptor engagement is a critical aspect of viral infection. This paper compares the dynamics of virus-receptor interactions for SARS-CoV (CoV1) and CoV2. At low (endosomal) pH, the binding free energy landscape of CoV1 and CoV2 interactions with the angiotensin-converting enzyme 2 (ACE2) receptor is almost the same. However, at neutral pH the landscape is different due to the loss of a pH-switch (His445Lys) in the receptor binding domain (RBD) of CoV2 relative to CoV1. Namely, CoV1 stabilizes a transition state above the bound state. In situations where small external strains are applied by, say, shear flow in the respiratory system, the off rate of the viral particle is enhanced. As a result, CoV1 virions are expected to detach from cell surfaces in time scales that are much faster than the time needed for other receptors to reach out and stabilize virus attachment. On the other hand, the loss of this pH-switch, which sequence alignments show is unique to CoV2, eliminates the transition state and allows the virus to stay bound to the ACE2 receptor for time scales compatible with the recruitment of additional ACE2 receptors diffusing in the cell membrane. This has important implications for viral infection and its pathology. CoV1 does not trigger high infectivity in the nasal area because it either rapidly drifts down the respiratory tract or is exhaled. By contrast, this novel mutation in CoV2 should not only retain the infection in the nasal cavity until ACE2-rich cells are sufficiently depleted, but also require fewer particles for infection. This mechanism explains observed longer incubation times, extended period of viral shedding, and higher rate of transmission. These considerations governing viral entry suggest that number of ACE2-rich cells in human nasal mucosa, which should be significantly smaller for children (and females relative to males), should also correlate with onset of viral load that could be a determinant of higher virus susceptibility. Critical implications for the development of new vaccines to combat current and future pandemics that, like SARS-CoV2, export evolutionarily successful strains via higher transmission rates by viral retention in nasal epithelium are also discussed.

Loss of pH switch unique to SARS-CoV2 supports unfamiliar virus pathology

The spatial distribution of the COVID-19 infection in China cannot be explained solely by geographical distance and regulatory stringency. In this research we investigate how meteorological conditions and air pollution, as concurring factors, impact COVID-19 transmission, using data on new confirmed cases from 219 prefecture cities from January 24 to February 29, 2020. Results revealed a kind of nonlinear dose-response relationship between temperature and coronavirus transmission. We also found that air pollution indicators are positively correlated with new confirmed cases, and the coronavirus further spreads by 5-7% as the AQI increases by 10 units. Further analysis based on regional divisions revealed that in northern China the negative effects of rising temperature on COVID-19 is counteracted by aggravated air pollution. In the southern cities, the ambient temperature and air pollution have a negative interactive effect on COVID-19 transmission, implying that rising temperature restrains the facilitating effects of air pollution and that they jointly lead to a decrease in new confirmed cases. These results provide implications for the control and prevention of this disease and for the anticipation of another possible pandemic.

Effects of meteorological conditions and air pollution on COVID-19 transmission: Evidence from 219 Chinese cities.

Abstract The coronavirus pandemic, which has numerous global implications, has led people to believe that nothing will be the same as before. The present day is dominated by studies on determining the factors that affect, taking preventive actions, and trying to find an effective treatment on top priority. Meteorological parameters are among the crucial factors affecting infectious diseases. The present study examines the correlation between weather and coronavirus disease 2019 (COVID-19) by considering nine cities in Turkey. In this regard, temperature (°C), dew point (°C), humidity (%), and wind speed (mph) are considered as parameters of weather. Research states that the incubation period of COVID-19 varies from 1 day to 14 days. Therefore, the effects of each parameter within 1, 3, 7, and 14 days are examined. In addition, the population is included as an effective parameter for evaluation. The analyses are conducted based on Spearman's correlation coefficients. The results showed that the highest correlations were observed for population, wind speed 14 days ago, and temperature on the day, respectively. The study results may guide authorities and decision-makers on taking specific measures for the cities.

Impact of weather on COVID-19 pandemic in Turkey

The novel coronavirus (COVID-19) has already spread to almost every country in the world and has infected over 3 million people. To understand the transmission mechanism of this highly contagious virus, it is necessary to study the potential factors, including meteorological conditions. Here, we present a machine learning approach to study the effect of temperature, humidity and wind speed on the number of infected people in the three most populous autonomous communities in Spain. We find that there is a moderate inverse correlation between temperature and the daily number of infections. This correlation manifests for temperatures recorded up to 6 days before the onset, which corresponds well to the known mean incubation period of COVID-19. We also show that the correlation for humidity and wind speed is not significant.

Effect of Temperature on the Transmission of COVID-19: A Machine Learning Case Study in Spain

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.

Abstract Coronaviruses (CoV) are a large family of viruses causing a spectrum of disease ranging from the common cold to more severe diseases as Middle East Respiratory Syndrome (MERS-CoV) and Severe Acute Respiratory Syndrome (SARS-CoV). The recent outbreak of coronavirus disease 2019 (COVID-19) has become a public health emergency worldwide. SARS-CoV-2, the virus responsible for COVID-19, is spread by human-to-human transmission via droplets or direct contact. However, since SARS-CoV-2 (as well as other coronaviruses) has been found in the fecal samples and anal swabs of some patients, the possibility of fecal-oral (including waterborne) transmission need to be investigated and clarified. This scoping review was conducted to summarize research data on CoV in water environments. A literature survey was conducted using the electronic databases PubMed, EMBASE, and Web Science Core Collection. This comprehensive research yielded more than 3000 records, but only 12 met the criteria and were included and discussed in this review. In detail, the review captured relevant studies investigating three main areas: 1) CoV persistence/survival in waters; 2) CoV occurrence in water environments; 3) methods for recovery of CoV from waters. The data available suggest that: i) CoV seems to have a low stability in the environment and is very sensitive to oxidants, like chlorine; ii) CoV appears to be inactivated significantly faster in water than non-enveloped human enteric viruses with known waterborne transmission; iii) temperature is an important factor influencing viral survival (the titer of infectious virus declines more rapidly at 23°C–25 °C than at 4 °C); iv) there is no current evidence that human coronaviruses are present in surface or ground waters or are transmitted through contaminated drinking-water; v) further research is needed to adapt to enveloped viruses the methods commonly used for sampling and concentration of enteric, non enveloped viruses from water environments. The evidence-based knowledge reported in this paper is useful to support risk analysis processes within the drinking and wastewater chain (i.e., water and sanitation safety planning) to protect human health from exposure to coronavirus through water.

Background: Most people raise a similar concern during this tough time of the COVID-19 pandemic caused by SARS-CoV-2 infection regarding when this outbreak will come to end. A recent thorough-general study on the success of China dealing with COVID-19 outbreak has concluded to recommend the need for a multi-sectoral approach to prevent future outbreaks of emerging infectious diseases including for the still-occurring COVID-19 outbreak with the initiative for the highest interest of the health of mankind Discussion: The prevalence of SARS-CoV as the predecessor of SARS-CoV-2 has been concluded to be more suitable in spring than autumn and winter, with nothing prevalence in summer. No coincidence that SARS-CoV-2 infection has outbreak around the world from January 2020 to the present, April 2020, as ever predicted to reoccur based on its predecessor, SARS-CoV, that have prevalence been high since January, February, March, April, until early May 2003. As opposed to other seasons, summer has low atmospheric pressure as its exemption that provenly causes virus inactivation. Conclusions: The denotative nature of SARS-CoV-2 seems to reflect its predecessor, SARS-CoV, which begins nearing the end of the year and reaches its optimum hence in spring, thereafter, finally ends in summer. Low atmospheric pressure in the summer impresses that it is the potential cause of ending the outbreak by deactivating SARS-CoV-2, apart from the hot temperature of weather. The knowledge to be gained here is further closely correlated to the fact that coronavirus is able to have genetic recombination that may bring about new genotypes and, consequently, outbreaks later occurring.

Any contribution of the season change to the spread of covid-19 caused by sars-cov-2?

This paper investigates the correlation between the high level of coronavirus SARS-CoV-2 infection accelerated transmission and lethality, and surface air pollution in Milan metropolitan area, Lombardy region in Italy. For January-April 2020 period, time series of daily average inhalable gaseous pollutants ozone (O3) and nitrogen dioxide (NO2), together climate variables (air temperature, relative humidity, wind speed, precipitation rate, atmospheric pressure field and Planetary Boundary Layer) were analyzed. In spite of being considered primarily transmitted by indoor bioaerosols droplets and infected surfaces or direct human-to-human personal contacts, it seems that high levels of urban air pollution, and climate conditions have a significant impact on SARS-CoV-2 diffusion. Exhibited positive correlations of ambient ozone levels and negative correlations of NO2 with the increased rates of COVID-19 infections (Total number, Daily New positive and Total Deaths cases), can be attributed to airborne bioaerosols distribution. The results show positive correlation of daily averaged O3 with air temperature and inversely correlations with relative humidity and precipitation rates. Viral genome contains distinctive features, including a unique N-terminal fragment within the spike protein, which allows coronavirus attachment on ambient air pollutants. At this moment it is not clear if through airborne diffusion, in the presence of outdoor and indoor aerosols, this protein "spike" of the new COVID-19 is involved in the infectious agent transmission from a reservoir to a susceptible host during the highest nosocomial outbreak in some agglomerated industrialized urban areas like Milan is. Also, in spite of collected data for cold season (winter-early spring) period, when usually ozone levels have lower values than in summer, the findings of this study support possibility as O3 can acts as a COVID-19 virus incubator. Being a novel pandemic coronavirus version, it might be ongoing during summer conditions associated with higher air temperatures, low relative humidity and precipitation levels.

Assessing the relationship between ground levels of ozone (O3) and nitrogen dioxide (NO2) with coronavirus (COVID-19) in Milan, Italy

The stability of human coronavirus 229E infectivity was maximum at pH 6.0 when incubated at either 4 or 33 degrees C. However, the influence of pH was more pronounced at 33 degrees C. Viral infectivity was completely lost after a 14-day incubation period at 22, 33, or 37 degrees C but remained relatively constant at 4 degrees C for the same length of time. Finally, the infectious titer did not show any significant reduction when subjected to 25 cycles of thawing and freezing. These studies will contribute to optimize virus growth and storage conditions, which will facilitate the molecular characterization of this important pathogen.

Effect of pH and temperature on the infectivity of human coronavirus 229E.

Association of COVID-19 pandemic with meteorological parameters over Singapore

Shedding ultraviolet light on coronavirus

Previous research has identified a relationship between climate and occurrence of SARS-CoV and MERS-CoV cases, information that can be used to reduce the risk of infection. Using COVID-19 notification and postcode data from New South Wales, Australia during the exponential phase of the epidemic in 2020, we used time series analysis to investigate the relationship between 749 cases of locally acquired COVID-19 and daily rainfall, 9 a.m. and 3 p.m. temperature, and 9 a.m. and 3 p.m. relative humidity. Lower 9 a.m. relative humidity (but not rainfall or temperature) was associated with increased case occurrence; a reduction in relative humidity of 1% was predicted to be associated with an increase of COVID-19 cases by 6.11%. During periods of low relative humidity, the public health system should anticipate an increased number of COVID-19 cases.

The role of climate during the COVID-19 epidemic in New South Wales, Australia

Effects of meteorological conditions and air pollution on COVID-19 transmission: Evidence from 219 Chinese cities

The pandemic of the COVID-19 disease extended from China across the north-temperate zone, and more recently to the tropics and southern hemisphere. We find no evidence that spread rates decline with temperatures above 20 oC, suggesting that the COVID-19 disease is unlikely to behave as a seasonal respiratory virus.

No Evidence for Temperature-Dependence of the COVID-19 Epidemic

This paper investigates whether the Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) pandemic could have been favored by specific weather conditions and other factors. It is found that the 2020 winter weather in the region of Wuhan (Hubei, Central China)—where the virus first broke out in December and spread widely from January to February 2020—was strikingly similar to that of the Northern Italian provinces of Milan, Brescia and Bergamo, where the pandemic broke out from February to March. The statistical analysis was extended to cover the United States of America, which overtook Italy and China as the country with the highest number of confirmed COronaVIrus Disease 19 (COVID-19) cases, and then to the entire world. The found correlation patterns suggest that the COVID-19 lethality significantly worsens (4 times on average) under weather temperatures between 4 °C and 12 °C and relative humidity between 60% and 80%. Possible co-factors such as median population age and air pollution were also investigated suggesting an important influence of the former but not of the latter, at least, on a synoptic scale. Based on these results, specific isotherm world maps were generated to locate, month by month, the world regions that share similar temperature ranges. From February to March, the 4–12 °C isotherm zone extended mostly from Central China toward Iran, Turkey, West-Mediterranean Europe (Italy, Spain and France) up to the United State of America, optimally coinciding with the geographic regions most affected by the pandemic from February to March. It is predicted that in the spring, as the weather gets warm, the pandemic will likely worsen in northern regions (United Kingdom, Germany, East Europe, Russia and North America) while the situation will likely improve in the southern regions (Italy and Spain). However, in autumn, the pandemic could come back and affect the same regions again. The Tropical Zone and the entire Southern Hemisphere, but in restricted colder southern regions, could avoid a strong pandemic because of the sufficiently warm weather during the entire year and because of the lower median age of their population. Google-Earth-Pro interactive-maps covering the entire world are provided as supplementary files.

Distribution of the SARS-CoV-2 Pandemic and Its Monthly Forecast Based on Seasonal Climate Patterns

The world is facing, while writing this review, a global pandemic due to one of the types of the coronaviruses (i.e., COVID-19), which is a new virus. Among the most important reasons for the transmission of infection between humans is the presence of this virus active on the surfaces and materials. Here, we addressed important questions such as do coronaviruses remain active on the inanimate surfaces? Do the types of inanimate surfaces affect the activity of coronaviruses? What are the most suitable ingredients that used to inactivate viruses? This review article addressed many of the works that were done in the previous periods on the survival of many viruses from the coronaviruses family on various surfaces such as steel, glass, plastic, Teflon, ceramic tiles, silicon rubber and stainless steel copper alloys, Al surface, sterile sponges, surgical gloves and sterile latex. The impacts of environmental conditions such as temperature and humidity were presented and discussed. The most important active ingredients that can deactivate viruses on the surfaces were reported here. We hope that these active ingredients will have the same effect on COVID-19.

Coronaviruses widespread on nonliving surfaces: important questions and promising answers

COVID-19 is having a great impact on public health, mortality and economy worldwide, in spite of the efforts to prevent its epidemy. The SARS-CoV-2 genome is different from that of MERS-CoV and SARS-CoV, although also expected to spread differently according to meteorological conditions. Our main goal is to investigate the role of some meteorological variables on the expansion of this outbreak. In this study, an exponential model relating the number of accumulated confirmed cases and time was considered. The rate of COVID-19 spread, using as criterion the doubling time of the number of confirmed cases, was used as dependent variable in a linear model that took four independent meteorological variables: temperature, humidity, precipitation and wind speed. Only China cases were considered, to control both cultural aspects and containment policies. Confirmed cases and the 4 meteorological variables were gathered between January 23 and March 1 (39 days) for the 31 provinces of Mainland China. Several periods of time were sampled for each province, obtaining more than one value for the rate of disease progression. Two different periods of time were tested, of 12 and 15 days, along with 3 and 5 different starting points in time, randomly chosen. The median value for each meteorological variable was computed, using the same time period; models with adjusted R square above 0.75 were selected. The rate of progression and doubling time were computed and used to fit a linear regression model. Models were evaluated using alpha=0.05. Results indicate that the doubling time correlates positively with temperature and inversely with humidity, suggesting that a decrease in the rate of progression of COVID-19 with the arrival of spring and summer in the north hemisphere. A 20oC increase is expected to delay the doubling time in 1.8 days. Those variables explain 18% of the variation in disease doubling time; the remaining 82% may be related to containment measures, general health policies, population density, transportation or cultural aspects.

Role of temperature and humidity in the modulation of the doubling time of COVID-19 cases

Abstract Meteorological parameters are the critical factors affecting the transmission of infectious diseases such as Middle East Respiratory Syndrome (MERS), Severe Acute Respiratory Syndrome (SARS), and influenza. Consequently, infectious disease incidence rates are likely to be influenced by the weather change. This study investigates the role of Singapore's hot tropical weather in COVID-19 transmission by exploring the association between meteorological parameters and the COVID-19 pandemic cases in Singapore. This study uses the secondary data of COVID-19 daily cases from the webpage of Ministry of Health (MOH), Singapore. Spearman and Kendall rank correlation tests were used to investigate the correlation between COVID-19 and meteorological parameters. Temperature, dew point, relative humidity, absolute humidity, and water vapor showed positive significant correlation with COVID-19 pandemic. These results will help the epidemiologists to understand the behavior of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus against meteorological variables. This study finding would be also a useful supplement to help the local healthcare policymakers, Center for Disease Control (CDC), and the World Health Organization (WHO) in the process of strategy making to combat COVID-19 in Singapore.

The present study presents a view on exploring the relationship pattern between COVID 19 daily cases with weather parameters and air pollutants in mainland India. We consider mean temperature, relative humidity, solar radiation, rainfall, wind speed, PM2.5, PM10, SO2, NO2 and CO as independent variable and daily COVID 19 cases as dependent variable for 18 states during 18th march to 30th April, 2020.After dividing the dataset for 0 to 10 day, 10 to 25 days and 0 to 44 days, the current study applied Akaike s Information Criteria (AIC) and Generalized Additive Model (GAM) to examine the kind of relationship between independent variables with COVID 19 cases. Initially GAM model result shows variables like temperature and solar radiation has positive relation (p<0.05) in 0 to 10 days study with daily cases. In 25 days dataset it significantly shows that temperature has positive relation above 23 degree centigrade, SO2 has a negative relationship and relative humidity has negative (between 30% to 45% and > 60%) and a positive relationship (45% to 60%) with COVID 19 cases (p=0.05). 44 days dataset has six parameters includes temperature as positive, relative humidity as negative (between 0 to 45%) and then positive (after >45%), NO2 as Positive (0 to 35 microgram/m3) followed by negative trend (after > 40 microgram/m3), SO2 and rainfall as negative relation. After sensitive analysis, it is found that weather variables like relative humidity, solar radiation and rainfall are more sensitive than temperature and wind speed. Whereas pollutants like NO2, PM2.5, PM10 and CO are more sensitive variables than SO2 in this study. In summary this study finds temperature, relative humidity, solar radiation, wind speed, SO2, PM2.5, and CO may be important factors associated with COVID 19 pandemic. Keywords: Weather parameter, Air pollutants, Daily COVID 19 cases, Akaike s Information Criteria (AIC), Generalized Additive Model (GAM) and Sensitive analysis.

Examine the impact of weather and ambient air pollutant parameters on daily case of COVID-19 in India.

Potential Impact of Climate on Novel Corona Virus (COVID-19) Epidemic

COVID-19 is a new type of coronavirus disease which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It originated in China in the month of December 2019 and quickly started to spread within the country. On 31st December 2019, it was first reported to country office of World Health Organization (WHO) in China. Since then, it has spread to most of the countries around the globe. However, there has been a recent rise in trend in believing that it would go away during summer days, which has not yet been properly investigated. In this paper, relationship of daily number of confirmed cases of COVID-19 with three environmental factors, viz. maximum relative humidity (RH_max), maximum temperature (T_max) and highest wind speed (WS_max), considering the incubation period, have been investigated statistically, for four of the most affected places of China, viz. Beijing, Chongqing, Shanghai, Wuhan and five of the most affected places of Italy, viz. Bergamo, Cremona, Lodi, Milano. It has been found that the relationship with maximum relative humidity and highest wind is mostly negligible, whereas relationship with maximum temperature is ranging between negligible to moderate.

Statistical investigation of relationship between spread of coronavirus disease (COVID-19) and environmental factors based on study of four mostly affected places of China and five mostly affected places of Italy

Coronaviruses widespread on nonliving surfaces: important questions and promising answers.

The seasonal cycle of respiratory viral diseases has been widely recognized for thousands of years, as annual epidemics of the common cold and influenza disease hit the human population like clockwork in the winter season in temperate regions. Moreover, epidemics caused by viruses such as severe acute respiratory syndrome coronavirus (SARS-CoV) and the newly emerging SARS-CoV-2 occur during the winter months. The mechanisms underlying the seasonal nature of respiratory viral infections have been examined and debated for many years. The two major contributing factors are the changes in environmental parameters and human behavior. Studies have revealed the effect of temperature and humidity on respiratory virus stability and transmission rates. More recent research highlights the importance of the environmental factors, especially temperature and humidity, in modulating host intrinsic, innate, and adaptive immune responses to viral infections in the respiratory tract. Here we review evidence of how outdoor and indoor climates are linked to the seasonality of viral respiratory infections. We further discuss determinants of host response in the seasonality of respiratory viruses by highlighting recent studies in the field. Expected final online publication date for the Annual Review of Virology, Volume 7 is September 29, 2020. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Seasonality of Respiratory Viral Infections.

This study aimed to evaluate the relationship between weather factors (temperature, humidity, solar radiation, wind speed, and rainfall) and COVID-19 infection in the State of Rio de Janeiro, Brazil. Solar radiation showed a strong (-0.609, p < 0.01) negative correlation with the incidence of novel coronavirus (SARS-CoV-2). Temperature (maximum and average) and wind speed showed negative correlation (p < 0.01). Therefore, in this studied tropical state, high solar radiation can be indicated as the main climatic factor that suppress the spread of COVID-19. High temperatures, and wind speed also are potential factors. Therefore, the findings of this study show the ability to improve the organizational system of strategies to combat the pandemic in the State of Rio de Janeiro, Brazil, and other tropical countries around the word.

Relationship between COVID-19 and weather: Case study in a tropical country

Abstract This paper investigates the correlation between the high level of coronavirus SARS-CoV-2 infection accelerated transmission and lethality, and surface air pollution in Milan metropolitan area, Lombardy region in Italy. For January–April 2020 period, time series of daily average inhalable gaseous pollutants ozone (O3) and nitrogen dioxide (NO2), together climate variables (air temperature, relative humidity, wind speed, precipitation rate, atmospheric pressure field and Planetary Boundary Layer) were analyzed. In spite of being considered primarily transmitted by indoor bioaerosols droplets and infected surfaces or direct human-to-human personal contacts, it seems that high levels of urban air pollution, and climate conditions have a significant impact on SARS-CoV-2 diffusion. Exhibited positive correlations of ambient ozone levels and negative correlations of NO2 with the increased rates of COVID-19 infections (Total number, Daily New positive and Total Deaths cases), can be attributed to airborne bioaerosols distribution. The results show positive correlation of daily averaged O3 with air temperature and inversely correlations with relative humidity and precipitation rates. Viral genome contains distinctive features, including a unique N-terminal fragment within the spike protein, which allows coronavirus attachment on ambient air pollutants. At this moment it is not clear if through airborne diffusion, in the presence of outdoor and indoor aerosols, this protein “spike” of the new COVID-19 is involved in the infectious agent transmission from a reservoir to a susceptible host during the highest nosocomial outbreak in some agglomerated industrialized urban areas like Milan is. Also, in spite of collected data for cold season (winter-early spring) period, when usually ozone levels have lower values than in summer, the findings of this study support possibility as O3 can acts as a COVID-19 virus incubator. Being a novel pandemic coronavirus version, it might be ongoing during summer conditions associated with higher air temperatures, low relative humidity and precipitation levels.

Host shifts - where a pathogen jumps between different host species - are an important source of emerging infectious disease. With ongoing climate change there is an increasing need to understand the effect changes in temperature may have on emerging infectious disease. We investigated whether species’ susceptibilities change with temperature and ask if susceptibility is greatest at different temperatures in different species. We infected 45 species of Drosophilidae with an RNA virus and measured how viral load changes with temperature. We found the host phylogeny explained a large proportion of the variation in viral load at each temperature, with strong phylogenetic correlations between viral loads across temperature. The variance in viral load increased with temperature, whilst the mean viral load did not, such that as temperature increased the most susceptible species become more susceptible, and the least susceptible less so. We found no significant relationship between a species’ susceptibility across temperatures and proxies for thermal optima; critical thermal maximum and minimum or basal metabolic rate. These results suggest that whilst the rank order of species susceptibilities can remain the same with changes in temperature, the likelihood of host shifts into a given species may increase or decrease. Author Summary Emerging infectious diseases are often the result of a host shift, where a pathogen jumps from one host species into another. Understanding the factors underlying host shifts is a major goal for infectious disease researchers. This effort has been further complicated by the fact that host-parasite interactions are now taking place in a period of unprecedented global climatic warming. Here, we ask how host shifts are affected by temperature by carrying out experimental infections using an RNA virus across a wide range of related species, at three different temperatures. We find that as temperature increases the most susceptible species become more susceptible, and the least susceptible less so. This has important consequences for our understanding of host shift events in a changing climate, and suggests that temperature changes may affect the likelihood of a host shift into certain species.

Changes in temperature alter susceptibility to a virus following a host shift

BACKGROUND The outbreak of the new coronavirus infection in Wuhan City, Hubei Province in December 2019, poses a huge threat to China and even global public health security. Respiratory droplets and contact transmission are the main routes of transmission of new coronaviruses. Compared with SARS and Ebola viruses, new coronavirus infections are infectious during the incubation period. Traditional SEIR (susceptibility-exposure-infection-Removal) There are some differences in conditions for the prediction of the epidemic trend of new coronavirus infection. The outbreak of the new coronavirus infection coincided with the Spring Festival before and after the Chinese Spring Festival.It is necessary to make appropriate optimization and amendments to the traditional model to meet the actual evolution of the epidemic situation. METHODS The traditional SEIR model assumes that the virus-infected person is not infectious during the incubation period and that the infected person did not take isolation measures during the illness. The transmission of the new coronavirus no longer meets the basic assumptions of the classical kinetic system. Therefore, this article first establishes a modified SEIR model. Predict and analyze the changing trend of the epidemic situation, then estimate the parameters involved in the infection dynamics model, and then use Matlab to simulate the established dynamic equations based on public data and analyze the results. Recommendations for universal prevention and control of infectious diseases. RESULTS The first case of new coronavirus infection was confirmed in Wuhan on December 8, 2019. When Wuhan City took no action, assuming the average daily number of contacts per infected person k = 5, the number of infected persons will reach about 2,384,803 people; If wuhan adopts the measures of sealing the city on January 22, 2020, under the premise of k=2, the number of infected people decreases by 19,773 compared with that on January 23, and there is no significant change in the time when the number of infected people reaches the peak. Under the premise of k = 1, the number of infected persons was reduced by 14,330 compared with the closure on January 23, and the time to reach the peak of the number of infected persons was reduced by 2 days. If Wuhan City is closed for one day, the number of infected persons will increase from 106,145 to 130,626 under the premise of k = 2; the number of infected persons will increase from 74,369 to 92,010 under the premise of k = 1. CONCLUSIONS Comparing the number of confirmed diagnoses actually notified by the department with the number of infected people obtained from the simulation of the model, it can be seen that the city closure measures adopted by the Wuhan Municipal Government on January 23 and the first-level response measures adopted by the country are effective for the epidemic Prevention and control play a vital role. Wearing a mask when going out and avoiding close contact with people can effectively reduce the infection rate.

Prediction of New Coronavirus Infection Based on a Modified SEIR Model

The coronavirus pandemic, which has numerous global implications, has led people to believe that nothing will be the same as before. The present day is dominated by studies on determining the factors that affect, taking preventive actions, and trying to find an effective treatment on top priority. Meteorological parameters are among the crucial factors affecting infectious diseases. The present study examines the correlation between weather and coronavirus disease 2019 (COVID-19) by considering nine cities in Turkey. In this regard, temperature (°C), dew point (°C), humidity (%), and wind speed (mph) are considered as parameters of weather. Research states that the incubation period of COVID-19 varies from 1â¯day to 14â¯days. Therefore, the effects of each parameter within 1, 3, 7, and 14â¯days are examined. In addition, the population is included as an effective parameter for evaluation. The analyses are conducted based on Spearman's correlation coefficients. The results showed that the highest correlations were observed for population, wind speed 14â¯days ago, and temperature on the day, respectively. The study results may guide authorities and decision-makers on taking specific measures for the cities.

Impact of weather on COVID-19 pandemic in Turkey

Global warming and the associated climate changes are predictable. They are enhanced by burning of fossil fuels and the emission of huge amounts of CO(2) gas which resulted in greenhouse effect. It is expected that the average global temperature will increase with 2–5 °C in the next decades. As a result, the earth will exhibit marked climatic changes characterized by extremer weather events in the coming decades, such as the increase in temperature, rainfall, summertime, droughts, more frequent and stronger tornadoes and hurricanes. Epidemiological disease cycle includes host, pathogen and in certain cases intermediate host/vector. A complex mixture of various environmental conditions (e.g. temperature and humidity) determines the suitable habitat/ecological niche for every vector host. The availability of suitable vectors is a precondition for the emergence of vector-borne pathogens. Climate changes and global warming will have catastrophic effects on human, animal and environmental ecosystems. Pathogens, especially neglected tropical disease agents, are expected to emerge and re-emerge in several countries including Europe and North America. The lives of millions of people especially in developing countries will be at risk in direct and indirect ways. In the present review, the role of climate changes in the spread of infectious agents and their vectors is discussed. Examples of the major emerging viral, bacterial and parasitic diseases are also summarized.

Climatic changes and their role in emergence and re-emergence of diseases

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an enveloped virus that may be sensitive to heat. We assessed whether the spread of coronavirus disease 2019 (COVID-19) correlates with air temperature. We also studied whether additional climate, geographical, and population variables were correlated. The total number of confirmed COVID-19 cases and mortality rates reported in each country between 1st Jan and 31st Mar 2020 were compared with the country's three-month average atmospheric air temperature, precipitation and latitude. Spearman's correlation coefficient (rs) was used to identify significant correlations. Our analysis included a total of 748,555 confirmed COVID-19 cases worldwide. The total number of patients with COVID-19 decreased with increasing atmospheric air temperature (rs = -0.54, 95%CI: [-0.64, -0.42]; P <0.001) and increased with an increasing latitude (rs =0.60, 95%CI: [0.48, 0.70]; P <0.001). Our findings justify further studies to examine the effect of air temperature on infectivity of SAR-CoV-2.

Correlation of the global spread of coronavirus disease-19 with atmospheric air temperature

Abstract Due to the close relationship between the incidence of infectious diseases by epidemics and environmental conditions, this research explores the temperature, evaporation, precipitation and regional climate effects on the local transmission of coronavirus SARS-CoV-2 inside 31 states and capital of Mexico since February 29 (national onset) to March 31, 2020. Statistical analysis was conducted to explore the association between the daily local COVID-19 confirmed positive cases (LCPC) and both climate characteristics and the daily weather reported by the regional meteorological stations. In this work, the local transmission ratio (LTR) was calculated with the regional LCPC divided by the number of the effective contagion days since regional onset in each state. The results showed a negative association between temperature (mean, max and min) and climate classification with both LCPC and LTR variables. The precipitation associated positively with LCPC and LTR. The associations between the climate classification with LCPC and LTR are statistically significant. The tropical climate (mean temperature around 25.95 °C and mean precipitation around 8.74 mm) delayed the regional onset. However, the regional onset in dry climates emerged earlier as consequence of the lower temperatures and higher precipitations (20.57 °C and 20.87 mm respectively) than the observed in the tropical climate. The fastest regional onsets were observed in tempered climates in states where the lowest temperatures and lowest precipitations were registered (19.65 °C and 8.48 mm respectively). Meteorological factors influenced the trend on the regional outbreaks in Mexican's states likely by the host predisposition and susceptibility during the cold winter season. In Mexico, the climate characteristics played a crucial role on the local infection during the phase 1 being the tempered regions (as Michoacán, Jalisco, Puebla, etc.) more vulnerable than the dry (as Chihuahua, Durango or Zacatecas, etc.) or tropical areas (as Colima, Campeche, Morelos etc.).

The temperature and regional climate effects on communitarian COVID-19 contagion in Mexico throughout phase 1

OBJECTIVE To understand the association between the SARS outbreak and the environmental temperature, and to provide a scientific basis for prevention and control measures against it. METHODS The daily numbers of the probable SARS patients and the daily meteorological factors during the SARS outbreak period in Hong Kong, Guangzhou, Beijing, and Taiyuan were used in the data analysis. Ecological analysis was conducted to explore the association between the daily numbers of probable SARS patients and the environmental temperature and its variations. RESULTS There was a significant correlation between the SARS cases and the environmental temperature seven days before the onset and the seven day time lag corresponds well with the known incubation period for SARS. The optimum environmental temperature associated with the SARS cases was between 16 degrees C to 28 degrees C, which may encourage virus growth. A sharp rise or decrease in the environmental temperature related to the cold spell led to an increase of the SARS cases because of the possible influence of the weather on the human immune system. This study provided some evidence that there is a higher possibility for SARS to reoccur in spring than that in autumn and winter. CONCLUSION Current knowledge based on case studies of the SARS outbreak in the four cities suggested that the SARS outbreaks were significantly associated with the temperature and its variations. However, because the fallacy and the uncontrolled confounding effects might have biased the results, the possibility of other meteorological factors having an affect on the SARS outbreaks deserves further investigation.

An initial investigation of the association between the SARS outbreak and weather: with the view of the environmental temperature and its variation.

The outbreak of coronavirus disease 2019 (COVID-19), caused by the virus SARS-CoV-2, has been rapidly increasing in the United States. Boroughs of New York City, including Queens county, turn out to be the epicenters of this infection. According to the data provided by the New York State Department of Health, most of the cases of new COVID-19 infections in New York City have been found in the Queens county where 42,023 people have tested positive, and 3221 people have died as of 20 April 2020. Person-to-person transmission and travels were implicated in the initial spread of the outbreaks, but factors related to the late phase of rapidly spreading outbreaks in March and April are still uncertain. A few previous studies have explored the links between air pollution and COVID-19 infections, but more data is needed to understand the effects of short-term exposures of air pollutants and meteorological factors on the spread of COVID-19 infections, particularly in the U.S. disease epicenters. In this study, we have focused on ozone and PM2.5, two major air pollutants in New York City, which were previously found to be associated with respiratory viral infections. The aim of our regression modeling was to explore the associations among ozone, PM2.5, daily meteorological variables (wind speed, temperature, relative humidity, absolute humidity, cloud percentages, and precipitation levels), and COVID-19 confirmed new cases and new deaths in Queens county, New York during March and April 2020. The results from these analyses showed that daily average temperature, daily maximum eight-hour ozone concentration, average relative humidity, and cloud percentages were significantly and positively associated with new confirmed cases related to COVID-19; none of these variables showed significant associations with new deaths related to COVID-19. The findings indicate that short-term exposures to ozone and other meteorological factors can influence COVID-19 transmission and initiation of the disease, but disease aggravation and mortality depend on other factors.

Short-Term Effects of Ambient Ozone, PM2.5, and Meteorological Factors on COVID-19 Confirmed Cases and Deaths in Queens, New York