Wind: a neglected factor in the spread of infectious diseases

Zika and Chikungunya in Europe 2100 - A GIS based model for risk estimation

BACKGROUND

The spread of vector-borne infectious diseases is determined, among other things, by temperature. Thus, climate change will have an influence on their global distribution. In the future, Europe will approach the temperature optimum for the transmission of ZIKV and CHIKV. Climate scenarios and climate models can be used to depict future climatic changes and to draw conclusions about future risk areas for vector-borne infectious diseases.

METHODS

Based on the RCP 4.5 and RCP 8.5 climate scenarios, a geospatial analysis was carried out for the future temperature suitability of ZIKV and CHIKV in Europe. The results were presented in maps and the percentage of the affected areas calculated.

RESULTS

Due to rising temperatures, the risk areas for transmission of ZIKV and CHIKV spread in both RCP scenarios. For CHIKV transmission, Spain, Portugal, the Mediterranean coast and areas near the Black Sea are mainly affected. Due to high temperatures, large areas throughout Europe are at risk for ZIKV and CHIKV transmission.

CONCLUSION

Temperature is only one of many factors influencing the spread of vector-borne infectious diseases. Nevertheless, the representation of risk areas on the basis of climate scenarios allows an assessment of future risk development. Monitoring and adaptation strategies are indispensable for coping with and containing possible future autochthonous transmissions and epidemics in Europe.

Patterns of Non-influenza Respiratory Viruses Among Severe Acute Respiratory Infection Cases in Burkina Faso: A Surveillance Study

BACKGROUND

Although influenza viruses cause only one-fifth of severe acute respiratory infections (SARI) in Burkina Faso, the other viral causes of SARI remain poorly investigated to inform clinical and preventive decision making.

METHODS

Between 2016 and 2019, we prospectively enrolled inpatients meeting the World Health Organization (WHO) case definition of SARI in Burkina Faso. Results of viral etiologies among inpatients tested negative for influenza using the Fast Track Diagnostics Respiratory Kits (FTD-33) were reported.

RESULTS

Of 1541 specimens tested, at least one respiratory virus was detected in 76.1% of the 1231 specimens negative for influenza virus. Human rhinoviruses (hRVs) were the most detected pathogens (476; 38.7%), followed by human adenoviruses (hAdV) (17.1%, 210/1231), human respiratory syncytial virus (hRSV) (15.4%, 189/1231), enterovirus (EnV) (11.2%, 138/1231), human bocavirus (hBoV) (7.9%, 97/1231), parainfluenza 3 (hPIV3) (6.1%, 75/1231), human metapneumovirus (hMPV) (6.0%,74/1321), parainfluenza 4 (hPIV4) (4.1%, 51/1231), human coronavirus OC43 (hCoV-OC43) (3.4%, 42/1231), human coronavirus HKU1(hCoV-HKU1) (2.7%, 33/1231), human coronavirus NL63 (hCoV-NL63) (2.5%, 31/1231), parainfluenza 1 (hPIV1) (2.0%, 25/1231), parainfluenza 2 (hPIV2) (1.8%, 22/1231), human parechovirus (PeV) (1.1%, 14/1231), and human coronavirus 229E (hCoV-229E) (0.9%, 11/1231). Among SARI cases, infants aged 1-4 years were mostly affected (50.7%; 622/1231), followed by those <1 year of age (35.7%; 438/1231). Most detected pathogens had year-long circulation patterns, with seasonal peaks mainly observed during the cold and dry seasons.

CONCLUSION

Several non-influenza viruses are cause of SARI in Burkina Faso. The integration of the most common pathogens into the routine influenza surveillance system might be beneficial.

Did unprecedented air pollution levels cause spike in Delhi's COVID cases during second wave?

The onset of the second wave of COVID-19 devastated many countries worldwide. Compared with the first wave, the second wave was more aggressive regarding infections and deaths. Numerous studies were conducted on the association of air pollutants and meteorological parameters during the first wave of COVID-19. However, little is known about their associations during the severe second wave of COVID-19. The present study is based on the air quality in Delhi during the second wave. Pollutant concentrations decreased during the lockdown period compared to pre-lockdown period (PM_2.5: 67 µg m^-3 (lockdown) versus 81 µg m^-3 (pre-lockdown); PM₁₀: 171 µg m^-3 versus 235 µg m^-3; CO: 0.9 mg m^-3 versus 1.1 mg m^-3) except ozone which increased during the lockdown period (57 µg m^-3 versus 39 µg m^-3). The variation in pollutant concentrations revealed that PM_2.5, PM₁₀ and CO were higher during the pre-COVID-19 period, followed by the second wave lockdown and the lowest in the first wave lockdown. These variations are corroborated by the spatiotemporal variability of the pollutants mapped using ArcGIS. During the lockdown period, the pollutants and meteorological variables explained 85% and 52% variability in COVID-19 confirmed cases and deaths (determined by General Linear Model). The results suggests that air pollution combined with meteorology acted as a driving force for the phenomenal growth of COVID-19 during the second wave. In addition to developing new drugs and vaccines, governments should focus on prediction models to better understand the effect of air pollution levels on COVID-19 cases. Policy and decision-makers can use the results from this study to implement the necessary guidelines for reducing air pollution. Also, the information presented here can help the public make informed decisions to improve the environment and human health significantly.

Synthesizing the connections between environmental disturbances and zoonotic spillover

Zoonotic spillover is a phenomenon characterized by the transfer of pathogens between different animal species. Most human emerging infectious diseases originate from non-human animals, and human-related environmental disturbances are the driving forces of the emergence of new human pathogens. Synthesizing the sequence of basic events involved in the emergence of new human pathogens is important for guiding the understanding, identification, and description of key aspects of human activities that can be changed to prevent new outbreaks, epidemics, and pandemics. This review synthesizes the connections between environmental disturbances and increased risk of spillover events based on the One Health perspective. Anthropogenic disturbances in the environment (e.g., deforestation, habitat fragmentation, biodiversity loss, wildlife exploitation) lead to changes in ecological niches, reduction of the dilution effect, increased contact between humans and other animals, changes in the incidence and load of pathogens in animal populations, and alterations in the abiotic factors of landscapes. These phenomena can increase the risk of spillover events and, potentially, facilitate new infectious disease outbreaks. Using Brazil as a study model, this review brings a discussion concerning anthropogenic activities in the Amazon region and their potential impacts on spillover risk and spread of emerging diseases in this region.

FMD virus spillover from domestic livestock caused outbreak in captive wild ungulates: First report from Pakistan

The potential spillover of foot and mouth disease (FMD) virus at the wildlife-livestock interface is mainly responsible for the outbreaks in captive wild ungulates. The current study was planned to investigate an FMD outbreak in the wild ungulate species in the Jallo Wildlife Park and breeding facility, Lahore, Pakistan from Mar 2021- Jun 2021. The disease was confirmed based on ELISA through the detection of antibodies against the non-structural protein of FMD virus and typical clinical signs of oral and feet lesions, and even partial or complete hoof shedding in severe cases. To investigate the possible cause of FMD spillover and its pattern, a series of interviews were conducted with wildlife practitioners, animal handlers, and the local veterinarians in villages adjacent to the park. The data revealed neither vaccination nor any FMD outbreak in the last 10 years. The epidemic curve and time-series analysis showed a mixed outbreak characterized by the introduction of disease and then propagative spread from infected to susceptible animals. After the first reports of clinical signs in Blackbuck, Urial and Mouflon sheep were infected while in the end, the cases were reported from the enclosures of Sambar deer and Spotted deer. The morbidity rate among all the wild ungulate species was 92% and the mean mortality rate was 27%. The study concluded that possible sources for primary disease incidence might be animal handlers having FMD infected animals in their houses and transport vehicles coming from adjacent disease-affected villages. For the disease spread between enclosures, another possibility of wind-borne FMD virus spread could also be considered. This is the first report regarding the FMD outbreak and its spillover pattern in captive wild ungulates in Pakistan. These findings will be helpful in understanding the importance of wildlife livestock interface in FMD transmission and to design effective strategies to control the disease.

Meteorological factors and non-pharmaceutical interventions explain local differences in the spread of SARS-CoV-2 in Austria

The drivers behind regional differences of SARS-CoV-2 spread on finer spatio-temporal scales are yet to be fully understood. Here we develop a data-driven modelling approach based on an age-structured compartmental model that compares 116 Austrian regions to a suitably chosen control set of regions to explain variations in local transmission rates through a combination of meteorological factors, non-pharmaceutical interventions and mobility. We find that more than 60% of the observed regional variations can be explained by these factors. Decreasing temperature and humidity, increasing cloudiness, precipitation and the absence of mitigation measures for public events are the strongest drivers for increased virus transmission, leading in combination to a doubling of the transmission rates compared to regions with more favourable weather. We conjecture that regions with little mitigation measures for large events that experience shifts toward unfavourable weather conditions are particularly predisposed as nucleation points for the next seasonal SARS-CoV-2 waves.

How weather modulates the spread of SARS-CoV-2 on fine spatio-temporal scales is still not fully understood. Here we use a controlled regional comparison to isolate the impact of five different meteorological factors, four types of non-pharmaceutical interventions as well as individual-level mobility on transmission rates in Austria. We find that more than 60% of regional variations can be explained by these factors. Temperature and humidity relate inversely with transmission rates whereas cloudiness and precipitation correlate with increasing transmission. We also observe a particularly strong impact of restrictions targeting large events. Our results suggest that a combination of weather shifts towards winter conditions combined with little mitigation measures for large gatherings drive the early growth of seasonal SARS-CoV-2 waves.

Exploring short term spatio-temporal pattern of PM2.5 and PM10 and their relationship with meteorological parameters during COVID-19 in Delhi

Present study aims to examine the impact of lockdown on spatio-temporal concentration of PM2.5 and PM10 - categorized and recorded based on its levels during pre-lockdown, lockdown and unlock phases while noting the relationship of these levels with meteorological parameters (temperature, wind speed, relative humidity, rainfall, pressure, sun hour and cloud cover) in Delhi. To aid the study, a comparison was made with the last two years (2018 to 2019), covering the same periods of pre-lockdown, lockdown and unlock phases of 2020. Correlation analysis, linear regression (LR) was used to examine the impact of meteorological parameters on particulate matter (PM) concentrations in Delhi, India. The findings showed that (i) substantial decline of PM concentration in Delhi during lockdown period, (ii) there were substantial seasonal variation of particulate matter concentration in city and (iii) meteorological parameters have close associations with PM concentrations. The findings will help planners and policy makers to understand the impact of air pollutants and meteorological parameters on infectious disease and to adopt effective strategies for future.

Health impacts of daily weather fluctuations: Empirical evidence from COVID-19 in U.S. counties

The emergence of the novel coronavirus has necessitated immense research efforts to understand how several non-environmental and environmental factors affect transmission. With the United States leading the path in terms of case incidence, it is important to investigate how weather variables influence the spread of the disease in the country. This paper assembles a detailed and comprehensive dataset comprising COVID-19 cases and climatological variables for all counties in the continental U.S. and uses a developed econometric approach to estimate the causal effect of certain weather factors on the growth rate of infection. The results indicate a non-linear and significant negative relationship between the individual weather measures and the growth rate of COVID-19 in the U.S. Specifically, the paper finds that a 1 °C rise in daily temperature will reduce daily covid growth rate in the U.S. by approximately 6 percent in the following week, while a marginal increase in relative humidity reduces the same outcome by 1 percent over a similar period. In comparison, a 1 m/s increase in daily wind speed will bring about an 8 percent drop in daily growth rate of COVID-19 in the country. These results differ by location and are robust to several sensitivity checks, so large deviations are unexpected.

Impact of the inversion and air pollution on the number of patients with Covid-19 in the metropolitan city of Tehran

There is a downward curve between increasing inversion altitude and the number of coronavirus patients during all periods. As temperature inversion altitude increases, the pollutants are dispersed in a greater thickness of the atmosphere and the concentration of the pollutants decreases on the earth's surface. At the same time, the number of patients with Covid-19 reduces. Although investigation of the effect of severity of pollutants on the number of coronavirus patients showed poor significance level during the periods, a decreasing and increasing relationship was shown. in 1- and 9-14-day periods, the correlation coefficient was negative. As a result, the effect of the severity of pollutants and Covid-19 is not observed on 1- and9-14-day periods. Conversely, during2-8-day periods, a positive correlation coefficient was observed. Therefore, the time between infection with the virus and the onset of symptoms of this disease is between 2 and 8 days, in which the 3-day period showed the highest correlation. Considering the relationship between inversion altitude, the severity of pollutants and the number of patients during 2-5-day periods, it can be concluded that in the metropolitan city of Tehran, the maximum infection of this virus and the onset of symptoms is between 2 and 5 days.

COVID-19 and the emerging research trends in environmental studies: a bibliometric evaluation

The ongoing pandemic of the coronavirus disease 2019 (COVID-19) is a global health emergency. Thousands of articles have been published to tackle this crisis. Here, a bibliometric study of the publications in environmental studies has been conducted to identify the emerging research trends in this field in the era of COVID-19. Bibliometric analysis serves as a useful tool to evaluate research productivity and scholarly trends in a field. For this, publications were searched in nine environment-related subject categories indexed in Science Citation Index Expanded (SCI-EXPANDED) database of the Web of Science Core Collection. A bibliometric evaluation of 495 relevant documents was performed to identify various essential research indicators, including the type of the publication, the most prominent journals, subject categories, authors, institutions, and the countries, that contributed significantly to this theme. Major focus of this bibliometric study is to illustrate the potential research hotspots emerged during this pandemic. It has been found that significant amount of research has been conducted for the assessment of environmental quality and its contribution in environmental transmission of COVID-19. In addition to its positive impacts on environment, COVID-19 has contributed indirectly in worsening many environmental threats such as increased exposure to disinfectants and antimicrobials, poor solid waste management, and food insecurity. Researchers have also been focusing on the strategies for the planning of post-COVID-19 cities and buildings and to protect the ecology. This bibliometric study allowed the visualization of research agenda in the field of environmental studies during this pandemic.

Non-linear correlation between daily new cases of COVID-19 and meteorological factors in 127 countries

Meteorological parameters are the critical factors of affecting respiratory infectious disease such as Middle East Respiratory Syndrome (MERS), Severe Acute Respiratory Syndrome (SARS) and influenza, however, the effect of meteorological parameters on coronavirus disease 2019 (COVID-19) remains controversial. This study investigated the effects of meteorological factors on daily new cases of COVID-19 in 127 countries, as of August 31 2020. The log-linear generalized additive model (GAM) was used to analyze the effect of meteorological variables on daily new cases of COVID-19. Our findings revealed that temperature, relative humidity, and wind speed are nonlinearly correlated with daily new cases, and they may be negatively correlated with the daily new cases of COVID-19 over 127 countries when temperature, relative humidity and wind speed were below 20°C, 70% and 7 m/s respectively. Temperature(>20°C) was positively correlated with daily new cases. Wind speed (when>7 m/s) and relative humidity (>70%) was not statistically associated with transmission of COVID-19. The results of this research will be a useful supplement to help healthcare policymakers in the Belt and Road countries, the Centers for Disease Control (CDC) and the World Health Organization (WHO) to develop strategies to combat COVID-19.

Control and prevention of infectious diseases from a One Health perspective

The ongoing COVID-19 pandemic has caught the attention of the global community and rekindled the debate about our ability to prevent and manage outbreaks, epidemics, and pandemics. Many alternatives are suggested to address these urgent issues. Some of them are quite interesting, but with little practical application in the short or medium term. To realistically control infectious diseases, human, animal, and environmental factors need to be considered together, based on the One Health perspective. In this article, we highlight the most effective initiatives for the control and prevention of infectious diseases: vaccination; environmental sanitation; vector control; social programs that encourage a reduction in the population growth; control of urbanization; safe sex stimulation; testing; treatment of sexually and vertically transmitted infections; promotion of personal hygiene practices; food safety and proper nutrition; reduction of the human contact with wildlife and livestock; reduction of social inequalities; infectious disease surveillance; and biodiversity preservation. Subsequently, this article highlights the impacts of human genetics on susceptibility to infections and disease progression, using the SARS-CoV-2 infection as a study model. Finally, actions focused on mitigation of outbreaks and epidemics and the importance of conservation of ecosystems and translational ecology as public health strategies are also discussed.

Variability in human attractiveness to mosquitoes

Blood-feeding mosquitoes locate humans spatially by detecting a combination of human-derived chemical signals, including carbon dioxide, lactic acid, and other volatile organic compounds. Mosquitoes use these signals to differentiate humans from other animals. Spatial abiotic factors (e.g. humidity, heat) are also used by mosquitoes to find a host. Mosquitoes cause discomfort and harm to humans, being vectors of many pathogens. However, not all humans suffer from mosquito bites with the same frequency or intensity. Some individuals are more attractive to mosquitoes than others, and this has an important impact on the risk of infection by pathogens transmitted by these vectors, such as arboviruses and malaria parasites. Variability in human attractiveness to mosquitoes is partially due to individual characteristics in the composition and intensity in the release of mosquito attractants. The factors that determine these particularities are diverse, modestly understood and still quite controversial. Thus, this review discusses the role of pregnancy, infection with malaria parasites (Plasmodium spp.), skin microbiota, diet, and genetics in human attractiveness to mosquitoes. In brief, pregnancy and Plasmodium infection increase the host attractiveness to mosquitoes. Skin microbiota and human genetics (especially HLA alleles) modulate the production of mosquito attractants and therefore influence individual susceptibility to these insects. There is evidence pointing to a role of diet on human susceptibility to mosquitoes, with some dietary components having a bigger influence than others. In the last part of the review, other factors affecting human-mosquito interactions are debated, with a special focus on the role of mosquito genetics, pathogens and environmental factors (e.g. wind, environmental disturbances). This work highlights that individual susceptibility to mosquitoes is composed of interactions of different human-associated components, environmental factors, and mosquito characteristics. Understanding the importance of these factors, and how they interact with each other, is essential for the development of better mosquito control strategies and studies focused on infectious disease dynamics.

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Individual human attractiveness to mosquitoes is highly variable.

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Mosquito attractants released into the air vary from person to person.

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Variation in attractiveness to mosquitoes alters the risk of mosquito-borne infections.

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Pregnancy, malaria infection, skin microbiota and genetic factors alter the release of mosquito attractants.

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Environment and mosquito-related factors affect human–mosquito interactions.

Effect of meteorological factors on COVID-19 cases in Bangladesh

This work is intended to examine the effects of Bangladesh's subtropical climate on coronavirus diseases 2019 (COVID-19) transmission. Secondary data for daily meteorological variables and COVID-19 cases from March 8 to May 31, 2020, were collected from the Bangladesh Meteorological Department (BMD) and Institute of Epidemiology, Disease Control and Research (IEDCR). Distributed lag nonlinear models, Pearson's correlation coefficient and wavelet transform coherence were employed to appraise the relationship between meteorological factors and COVID-19 cases. Significant coherence between meteorological variables and COVID-19 at various time-frequency bands has been identified in this work. The results showed that the minimum (MinT) and mean temperature, wind speed (WS), relative humidity (RH) and absolute humidity (AH) had a significant positive correlation while contact transmission had no direct association with the number of COVID-19 confirmed cases. When the MinT was 18 °C, the relative risk (RR) was the highest as 1.04 (95%CI 1.01-1.06) at lag day 11. For the WS, the highest RR was 1.03 (95% CI 1.00-1.07) at lag day 0, when the WS was 21 km/h. When RH was 46%, the highest RR was 1.00 (95% CI 0.98-1.01) at lag day 14. When AH was 23 g/m³, the highest RR was 1.05 (95% CI 1.01-1.09) at lag day 14. We found a profound effect of meteorological factors on SARS-CoV-2 transmission. These results will assist policymakers to know the behavioral pattern of the SARS-CoV-2 virus against meteorological indicators and thus assist to devise an effective policy to fight against COVID-19 in Bangladesh.

Spread of SARS-CoV-2 through Latin America and the Caribbean region: A look from its economic conditions, climate and air pollution indicators

We have evaluated the spread of SARS-CoV-2 through Latin America and the Caribbean (LAC) region by means of a correlation between climate and air pollution indicators, namely, average temperature, minimum temperature, maximum temperature, rainfall, average relative humidity, wind speed, and air pollution indicators PM10, PM2.5, and NO2 with the COVID-19 daily new cases and deaths. The study focuses in the following LAC cities: Mexico City (Mexico), Santo Domingo (Dominican Republic), San Juan (Puerto Rico), Bogotá (Colombia), Guayaquil (Ecuador), Manaus (Brazil), Lima (Perú), Santiago (Chile), São Paulo (Brazil) and Buenos Aires (Argentina). The results show that average temperature, minimum temperature, and air quality were significantly associated with the spread of COVID-19 in LAC. Additionally, humidity, wind speed and rainfall showed a significant relationship with daily cases, total cases and mortality for various cities. Income inequality and poverty levels were also considered as a variable for qualitative analysis. Our findings suggest that and income inequality and poverty levels in the cities analyzed were related to the spread of COVID-19 positive and negative, respectively. These results might help decision-makers to design future strategies to tackle the spread of COVID-19 in LAC and around the world.

Association of climatic factors with COVID-19 in Pakistan

INTRODUCTION

Environmental factors such as wind, temperature, humidity, and sun exposure are known to affect influenza and viruses such as severe acute respiratory syndrome (SARS) and Middle East Respiratory Syndrome (MERS) transmissions. COVID-19 is a new pandemic with very little information available about its transmission and association with environmental factors. The goal of this paper is to explore the association of environmental factors on daily incidence rate, mortality rate, and recoveries of COVID-19.

METHODS

The environmental data for humidity, temperature, wind, and sun exposure were recorded from metrological websites and COVID-19 data such as the daily incidence rate, death rate, and daily recovery were extracted from the government's official website available to the general public. The analysis for each outcome was adjusted for factors such as lock down status, nationwide events, and the number of daily tests performed. Analysis was completed with negative binominal regression log link using generalised linear modelling.

RESULTS

Daily temperature, sun exposure, wind, and humidity were not significantly associated with daily incidence rate. Temperature and nationwide social gatherings, although non-significant, showed trends towards a higher chance of incidence. An increase in the number of daily testing was significantly associated with higher COVID-19 incidences (effect size ranged from 2.17-9.96). No factors were significantly associated with daily death rates. Except for the province of Balochistan, a lower daily temperature was associated with a significantly higher daily recovery rate.

DISCUSSION

Environmental factors such as temperature, humidity, wind, and daily sun exposure were not consistently associated with COVID-19 incidence, death rates, or recovery. More policing about precautionary measures and ensuring diagnostic testing and accuracy are needed.

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

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.

Association of COVID-19 pandemic with meteorological parameters over Singapore

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.

Spread of COVID-19, Meteorological Conditions and Air Quality in the City of Buenos Aires, Argentina: Two Facets Observed during Its Pandemic Lockdown

This work studied the spread of COVID-19, the meteorological conditions and the air quality in a megacity from two viewpoints: (1) the correlation between meteorological and air quality (PM10 and NO2) variables with infections and deaths due COVID-19, and (2) the improvement in air quality. Both analyses were performed for the pandemic lockdown due to COVID-19 in the City of Buenos Aires (CABA), the capital and the largest city in Argentina. Daily data from temperature, rainfall, average relative humidity, wind speed, PM10, NO2, new cases and deaths due COVID-19 were analyzed. Our findings showed a significant correlation of meteorological and air quality variables with COVID-19 cases. The highest temperature correlation occurred before the confirmation day of new cases. PM10 presented the highest correlation within 13 to 15 days lag, while NO2 within 3 to 6 days lag. Also, reductions in PM10 and NO2 were observed. This study shows that exposure to air pollution was significantly correlated with an increased risk of becoming infected and dying due to COVID-19. Thus, these results show that the NO2 and PM10 levels in CABA can serve as one of the indicators to assess vulnerability to COVID-19. In addition, decision-makers can use this information to adopt strategies to restrict human mobility during the COVID-19 pandemic and future outbreaks of similar diseases in CABA.

Effects of temperature and humidity on the daily new cases and new deaths of COVID-19 in 166 countries

The coronavirus disease 2019 (COVID-19) pandemic is the defining global health crisis of our time and the greatest challenge facing the world. Meteorological parameters are reportedly crucial factors affecting respiratory infectious disease epidemics; however, the effect of meteorological parameters on COVID-19 remains controversial. This study investigated the effects of temperature and relative humidity on daily new cases and daily new deaths of COVID-19, which has useful implications for policymakers and the public. Daily data on meteorological conditions, new cases and new deaths of COVID-19 were collected for 166 countries (excluding China) as of March 27, 2020. Log-linear generalized additive model was used to analyze the effects of temperature and relative humidity on daily new cases and daily new deaths of COVID-19, with potential confounders controlled for, including wind speed, median age of the national population, Global Health Security Index, Human Development Index and population density. Our findings revealed that temperature and relative humidity were both negatively related to daily new cases and deaths. A 1 °C increase in temperature was associated with a 3.08% (95% CI: 1.53%, 4.63%) reduction in daily new cases and a 1.19% (95% CI: 0.44%, 1.95%) reduction in daily new deaths, whereas a 1% increase in relative humidity was associated with a 0.85% (95% CI: 0.51%, 1.19%) reduction in daily new cases and a 0.51% (95% CI: 0.34%, 0.67%) reduction in daily new deaths. The results remained robust when different lag structures and the sensitivity analysis were used. These findings provide preliminary evidence that the COVID-19 pandemic may be partially suppressed with temperature and humidity increases. However, active measures must be taken to control the source of infection, block transmission and prevent further spread of COVID-19.

Winter Is Coming: A Southern Hemisphere Perspective of the Environmental Drivers of SARS-CoV-2 and the Potential Seasonality of COVID-19

SARS-CoV-2 virus infections in humans were first reported in December 2019, the boreal winter. The resulting COVID-19 pandemic was declared by the WHO in March 2020. By July 2020, COVID-19 was present in 213 countries and territories, with over 12 million confirmed cases and over half a million attributed deaths. Knowledge of other viral respiratory diseases suggests that the transmission of SARS-CoV-2 could be modulated by seasonally varying environmental factors such as temperature and humidity. Many studies on the environmental sensitivity of COVID-19 are appearing online, and some have been published in peer-reviewed journals. Initially, these studies raised the hypothesis that climatic conditions would subdue the viral transmission rate in places entering the boreal summer, and that southern hemisphere countries would experience enhanced disease spread. For the latter, the COVID-19 peak would coincide with the peak of the influenza season, increasing misdiagnosis and placing an additional burden on health systems. In this review, we assess the evidence that environmental drivers are a significant factor in the trajectory of the COVID-19 pandemic, globally and regionally. We critically assessed 42 peer-reviewed and 80 preprint publications that met qualifying criteria. Since the disease has been prevalent for only half a year in the northern, and one-quarter of a year in the southern hemisphere, datasets capturing a full seasonal cycle in one locality are not yet available. Analyses based on space-for-time substitutions, i.e., using data from climatically distinct locations as a surrogate for seasonal progression, have been inconclusive. The reported studies present a strong northern bias. Socio-economic conditions peculiar to the 'Global South' have been omitted as confounding variables, thereby weakening evidence of environmental signals. We explore why research to date has failed to show convincing evidence for environmental modulation of COVID-19, and discuss directions for future research. We conclude that the evidence thus far suggests a weak modulation effect, currently overwhelmed by the scale and rate of the spread of COVID-19. Seasonally modulated transmission, if it exists, will be more evident in 2021 and subsequent years.

Spatio-temporal analysis of meteorological factors in abating the spread of COVID-19 in Africa

In Asia, Europe and South America, the role of atmospheric condition in aiding or abating the growth curve of COVID-19 has been analysed. However, no study to date has examined such climatic extensions for the growth or otherwise of the novel coronavirus in Africa. Africa, with a mostly relatively warmer temperature differs from other regions of the world and in addition, has recorded far fewer cases compared to Asian, Europeans and the Americans (North and South). It then becomes imperative to examine the influence of meteorological indices in the growth or otherwise of coronavirus diseases in Africa to establish whether findings on the climatic conditions-COVID-19 growth are regionally specific. In this study, we examined the influence of meteorological factors for aiding or abating the spread of the aerosolised pathogen of COVID-19 in Africa. We rely on the generalised additive model (GAM) and found wind speed to positively relate to COVID-19 growth while mean temperature and relative humidity to inversely relates to COVID-19 growth curve in Africa. We accounted for potential cofounders in the core GAM model and discuss policy implications.

VO, Yatoo MI, Tiwari R, Pathak M, Patel SK, Sah R, Rodriguez-Morales AJ, Ganesh B, Kumar P, Singh RK. Coronavirus Disease Pandemic (COVID-19): Challenges and a Global Perspective

The technology-driven world of the 21st century is currently confronted with a major threat to humankind, represented by the coronavirus disease (COVID-19) pandemic, caused by the severe acute respiratory syndrome, coronavirus-2 (SARS-CoV-2). As of now, COVID-19 has affected more than 6 million confirmed cases and took 0.39 million human lives. SARS-CoV-2 spreads much faster than its two ancestors, SARS-CoV and Middle East respiratory syndrome-CoV (MERS-CoV), but has low fatality rates. Our analyses speculate that the efficient replication and transmission of SARS-CoV-2 might be due to the high-density basic amino acid residues, preferably positioned in close proximity at both the furin-like cleavage sites (S1/S2 and S2') within the spike protein. Given the high genomic similarities of SARS-CoV-2 to bat SARS-like CoVs, it is likely that bats serve as a reservoir host for its progenitor. Women and children are less susceptible to SARS-CoV-2 infection, while the elderly and people with comorbidities are more prone to serious clinical outcomes, which may be associated with acute respiratory distress syndrome (ARDS) and cytokine storm. The cohesive approach amongst researchers across the globe has delivered high-end viral diagnostics. However, home-based point-of-care diagnostics are still under development, which may prove transformative in current COVID-19 pandemic containment. Similarly, vaccines and therapeutics against COVID-19 are currently in the pipeline for clinical trials. In this review, we discuss the noteworthy advancements, focusing on the etiological viral agent, comparative genomic analysis, population susceptibility, disease epidemiology and diagnosis, animal reservoirs, laboratory animal models, disease transmission, therapeutics, vaccine challenges, and disease mitigation measures.

Nonlinear effect of wind velocity on mumps in Shenzhen, China, 2013-2016

OBJECTIVES

Plenty of studies have shown that wind velocity has an influence on airborne diseases. There is, however, no consistent conclusion found on the relationship between wind velocity and mumps, and the regional heterogeneity has been largely neglected in previous studies. This study aims to explore the association between wind velocity and mumps in Shenzhen.

STUDY DESIGN

Ecological study.

METHODS

Sixteen subdistricts with the highest incidence rates of mumps were selected from Shenzhen city, and the multilevel distributed lag-nonlinear model was conducted to explore the relationship between mumps cases and wind velocity via the dlnm and lme4 packages of the software R 3.4.3.

RESULTS

In Shenzhen, a total of 16,997 mumps cases were reported between 2013 and 2016, and the means of daily rainfall, temperature, relative humidity, and 10 min wind velocity were 5.74 mm, 23.27 °C, 76.31% and 1.87 m/s, respectively. Obvious nonlinear correlation relationships of wind velocity and mumps risk were found, where a reverse-V curved shape was shown in the exposure dimension with the logRR value of mumps peaking at 2 m/s, and the type of nonlinear correlation varying with the levels of wind velocity in lag dimension with a peak at two lag weeks.

CONCLUSIONS

The lag and nonlinear association between wind velocity and number of mumps cases were examined, while there was no statistically significant associations for other meteorological factors accounting for the regional heterogeneity. Results from this study indicated that public health administrators could strengthen health education in schools on ventilation management to prevent and control mumps outbreaks.