Seasonality Of COVID-19 Research Articles

Seasonal theory of COVID-19; one-year observation

Objectives: SARS-CoV-2 infected over 100 million individuals worldwide during one year interval. With the increase in the number of cases and deaths, theories were adopted; one important theory was the seasonality of COVID-19. This study aimed to show the potential seasonality of SARS-CoV-2 over a period of one year (one winter/summer and one transition (spring/autumn) season). Methods: Data about the global incidence of the cases of one year interval and the doubling and halving time of cases for 10 countries were obtained from COVID intel Database, WHO website. Results: A peak in the number of COVID-19 cases and deaths during late autumn and winter months were observed along with some decrease in the number of cases and deaths during spring and summer. The average of doubling and halving time for the chosen countries varied across the sphere; the average doubling and halving time for (N°) countries were (264.14) and (52.64), respectively, while for (S°) countries were (20.91) and (148.40), respectively. Conclusion: The epidemiological triad, (virus longevity in the air and on surfaces, increased susceptibility of the human victim in cold and dry weather and changes in human social behavior between winter and summer), explains the seasonal changes of the SARS-CoV-2 characteristics. So far the data for SARS-CoV-2 lie on the same line for the seasonality theory as other viruses such as influenza and SARS-CoV, follow the seasonality theory (they slow down during the summer and rise during winter), yet, longer periods of observation are required to confirm this theory.

COVID-19 seasonality in temperate countries

IntroductionWhile the beneficial effect of vaccination, restrictive measures, and social distancing in reducing mortality due to SARS-CoV-2 is intuitive and taken for granted, seasonality (predictable fluctuation or pattern that recurs or repeats over a one-year period) is still poorly understood and insufficiently taken into consideration. We aimed to examine SARS-CoV-2 seasonality in countries with temperate climate. MethodsWe identified countries with temperate climate and extracted average country temperature data from the National Center for Environmental information and from the Climate Change Knowledge Portal. We obtained mortality and vaccination rates from an open access database. We used the stringency index derived from the Oxford COVID-19 Government Response Tracker to quantify restriction policies. We used Spearman's and rank-correlation non-parametric test coefficients to investigate the association between COVID-19 mortality and temperature values. We employed multivariate regression models to analyze how containment measures, vaccinations, and monthly temperatures affected COVID-19 mortality rates. ResultsThe time series for daily deaths per million inhabitants and average monthly temperatures of European countries and US states with a temperate climate had a negative correlation (p < 0.0001 for all countries, 0.40 < R < 0.86). When running multivariate regression models with country fixed effects, we noted that mortality rates were significantly lower when temperature were higher. Interestingly, when adding an interaction term between monthly temperatures and vaccination rates, we found that as monthly temperatures dropped, the effect of the vaccination campaign on mortality was larger than at higher temperatures. DiscussionDeaths attributed to SARS-CoV-2 decreased during the summer period in temperate countries. We found that the effect of vaccination rates on mortality was stronger when temperatures were lower. Stakeholders should consider seasonality in managing SARS-CoV-2 and future pandemics to minimize mortality, limit the pressure on hospitals and intensive care units while maintaining economic and social activities.

Sickness absence during the COVID-19 pandemic

The aim of this research was to perform comparative analysis of the publicly avaiable data of the Social Insurance Institution (ZUS) on sickness absence of insured persons in Poland in 2016-2021 (before the outbreak and during the COVID-19 pandemic).&#x0D; Materials and methods. The research material consisted of data from the Social Insurance Institution for the years 2016-2021 (Q1) concerning the sickness absence of the insured. Due to the publication of data in an aggregated form, quantitative analysis was performed instead of statistical analysis. The data used in the analysis included the number of insured persons, the number of people receiving sickness benefits, the number of issued medical certificates on temporary incapacity to work and the reasons for the incapacity to work.&#x0D; Results and Conclusion. Since the beginning of the COVID-19 pandemic, following numbers have increased compared to 2019: the number of people receiving sickness benefit in Poland (by 10%), the number of days of sickness absence (by 7%) and the number of issued medical certificates of temporary incapacity for work (by 4%). The largest increase in the number of beneficiaries, the number of days of sickness absence and the number of medical certificates was recorded in the Q4 of 2020 (respectively by 21%, 16% and 24% compared to Q4 of 2019). Due to COVID-19, 4.84 million days of sickness absence were used in 2020 – it was the tenth cause of absence.&#x0D; The largest changes in the number of people receiving sickness benefit and the number of days of sickness absence can be observed in Q1 and Q4, which may result from the seasonality of COVID-19 and the subsequent wave of infections. Importantly, COVID-19 is not the only factor contributing overall increase in the number of days of sickness absence in Poland – absence due to non-communicable diseases also increased during the pandemic.

Modeling COVID-19 with mean field evolutionary dynamics: Social distancing and seasonality

The coronavirus pandemic has been declared a world health emergency by the World Health Organization, which has raised the importance of an accurate epidemiological model to predict the evolution of COVID-19. In this paper, we propose mean field evolutionary dynamics (MFEDs), inspired by optimal transport theory and mean field games on graphs, to model the evolution of COVID-19. In the MFEDs, we derive the payoff functions for different individual states from the commonly used replicator dynamics (RDs) and employ them to govern the evolution of epidemics. We also compare epidemic modeling based on MFEDs with that based on RDs through numerical experiments. Moreover, we show the efficiency of the proposed MFED-based model by fitting it to the COVID-19 statistics of Wuhan, China. Finally, we analyze the effects of one-time social distancing as well as the seasonality of COVID-19 through the post-pandemic period.

The Challenges of Home-Based Learning in COVID-19 Season: An Overview of Rural School in Sabah, Malaysia

The Challenges of Home-Based Learning in COVID-19 Season: An Overview of Rural School in Sabah, Malaysia

Injury Rates in the National Football League During the 2020 COVID-19 Season

Objectives The National Football League (NFL) altered the 2020 season due to the COVID-19 pandemic, which resulted in cancelled preseason games and a dynamic regular season schedule to accommodate for cancelled games. The purpose of this study was to evaluate if the disrupted training and preseason schedule lead to increased injury rates as seen in other professional sports. We hypothesized that the overall injury rate would be higher in the 2020 season compared to the 2018-2019 seasons, and that this increase will affect all body regions equally. Methods : Publicly released NFL weekly injury reports were queried to identify players listed as out or placed on the injured reserve for at least one game in the 2018-2020 seasons. Injuries were categorized into upper extremity, lower extremity, spine/core, head, illness, not injury related and undisclosed injuries. Incidence per 1000 athlete exposures was calculated for the prior two seasons (2018-2019) and for the 2020 season separately. Percentage of injuries occurring in each position were calculated separately for the pre-COVID-19 (2018 and 2019) and post-COVID-19 (2020) cohorts. Incidence rate ratios (IRR) and confidence intervals were used to compare injury rates in 2018-2019 versus 2020. The z-test for proportions was used to determine significant differences between injury incidences Results : The overall incidence rate per 1000 athlete exposures in 2020 was not significantly different compared to pre-COVID-19 seasons (21.6 versus 23.1, IRR 0.94, 95% CI: 0.9-1.0 p>0.999). The proportion of injuries by position did not change before and after COVID-19 either (p>0.999). Out listings due to illness were significantly increased during the 2020 season (0.8 versus 0.3, IRR 2.8, 95% CI: 1.4-5.2, p=0.004). Conclusion The incidence of NFL injuries did not significantly change in 2020. The distribution of injuries did not change with respect to position.

Comment on “COVID-19, the Built Environment, and Health”

Comment on “COVID-19, the Built Environment, and Health”

Home Advantage and Audience Effect Analysis of Turkish Super League in Covid-19 Season

Covid-19 pandemic dramatically affected soccer. Many competitions played without an audience in the 2019/2020 season. The aim of this study was to analyze Points (P), Goals Forward (GF), and Goals Away (GA) per game in Turkish Super League (TSL), Premier League, Bundesliga, La Liga, and Serie A before (BP) and After Pandemic restrictions (AP) during the 2019/2020 season separately and together. The tables of five leagues were separated into two terms as BP and AP, and P, GF, and GA were calculated for each period. Average P, GF, and GA per game were statistically compared. Paired samples t-test and paired samples correlations were used for statistical analysis. The obtained results showed that home P and GA increased AP in TSL without statistical significance. In parallel, home P and GF increased AP in Premier League and La Liga and showed significant correlations (p&lt;0.05). In contrast, in Bundesliga and La Liga, home P and GF decreased AP with significant correlation (p&lt;0.05). In La Liga, away GA significantly decreased AP (p=0.010148*). When all results of all teams (n=98) were compared together, home P (r=0.4371; p=0.000007***) and GA decreased AP and showed significant correlations. Furthermore, away P (r=0.386661; p=0.000084***) and GF (r=0.505488; p=0.000001***) increased with significant correlation. These results showed that the Covid-19 pandemic dissimilarly affected different leagues. However, overall results showed that home performances decreased and away results increased AP.

Scientists Uncover the Seasonality of COVID-19

Researchers identify the environmental variables driving the seasonality of the novel coronavirus.

Indonesian household demand for essential animal proteins and their pattern of price volatility during the Covid-19 season

The consumption patterns of Indonesian households are around 85% derived from vegetable proteins and 15% from animal proteins. Furthermore, low-income households often find it challenging to fulfill their energy and protein needs. It is becoming a severe issue when the Covid-19 break in Indonesia and puts many essential animal protein commodities into an excellent uncertainty condition. Although it is accepted that the effectiveness of population growth, none have assessed the relationship with the price volatility that was formed by the Covid-19 issue. This research aims to develop an econometric model on essential animal food demand and how their price volatility trend during Covid-19. The Linear Expenditure System (LES) was chosen as an approach to describing the demand for food commodities from essential animal protein sources using SUSENAS data for the 2019 enumeration period, while the ARCH/GARCH model was used as an approach to describe the pattern of price volatility using set of consumer price data from January 2010 until August 2020 enumeration period. This research shows that the price elasticity of the essential animal protein sources of food commodities shows that all commodities are inelastic. At the same time, changes in the relationship between essential animal food commodities reflect an overall shift in the consumption of society towards essential animal food commodities themselves. On the other hand, there is a specific movement in price volatility toward an explosive term, which led to a great uncertainty that will face both of consumers and producers in the future.

Price volatility of maize and animal protein commodities in Indonesia during the Covid-19 season

The demand for corn in Indonesia is dominated as raw material for animal feed, so the high and low price of corn will have a big impact on the price of livestock products such as chicken and chicken eggs. The Covid-19 gives an impact on the uncertainty of food commodity prices. As we know, food price stability is one of the supports for maintaining a balance of production and consumer buying power. This study aims to analyze the price volatility of corn, chicken meat, and chicken eggs in Indonesia during the Covid-19 pandemic. The ARCH/GARCH model was used as an approach to analyzing volatility in the monthly prices of corn, chicken meat, and chicken eggs at the consumer level during the January 2011-June 2020 period. This research showed that the price of corn and chicken is categorized as high volatility category, while chicken eggs are a low volatility category with the form is asymmetric. It can be concluded that the price uncertainty faced by consumers in the future for corn and chicken meat will be bigger, while chicken eggs will be decreased. Therefore, it is expected that the government will make policies for maintaining the stability of food supply and prices.

Comparable seasonal pattern for COVID-19 and flu-like illnesses

BackgroundDuring the first wave of COVID-19 it was hypothesized that COVID-19 is subject to multi-wave seasonality, similar to Influenza-Like Illnesses since time immemorial. One year into the pandemic, we aimed to test the seasonality hypothesis for COVID-19. MethodsWe calculated the average annual time-series for Influenza-Like Illnesses based on incidence data from 2016 till 2019 in the Netherlands, and compared these with two COVID-19 time-series during 2020/2021 for the Netherlands. We plotted the time-series on a standardized logarithmic infection scale. Finally, we calculated correlation coefficients and used univariate regression analysis to estimate the strength of the association between the time-series of COVID-19 and Influenza-Like Illnesses. ResultsThe time-series for COVID-19 and Influenza-Like Illnesses were strongly and highly significantly correlated. The COVID-19 peaks were all during flu season, and lows were all in the opposing period. Finally, COVID-19 meets the multi-wave characteristics of earlier flu-like pandemics, namely a short first wave at the tail-end of a flu season, and a longer and more intense second wave during the subsequent flu season. ConclusionsWe conclude that seasonal patterns of COVID-19 incidence and Influenza-Like Illnesses incidence are highly similar, in a country in the temperate climate zone, such as the Netherlands. Further, the COVID-19 pandemic satisfies the criteria of earlier respiratory pandemics, namely a first wave that is short-lived at the tail-end of flu season, and a second wave that is longer and more severe.This seems to imply that the same factors that are driving the seasonality of Influenza-Like Illnesses are causing COVID-19 seasonality as well, such as solar radiation (UV), temperature, relative humidity, and subsequently seasonal allergens and allergies.

On the Environmental Determinants of COVID-19 Seasonality.

Viral respiratory diseases (VRDs), such as influenza and COVID‐19, are thought to spread faster during winter than during summer. It has been previously argued that cold and dry conditions are more conducive to the transmission of VRDs than warm and humid climates, although this relationship appears restricted to temperate regions and the causal relationship is not well understood. The severe acute respiratory syndrome coronavirus 2 causing COVID‐19 has emerged as a serious global public health problem after the first COVID‐19 reports in Wuhan, China, in late 2019. It is still unclear whether this novel respiratory disease will ultimately prove to be a seasonal endemic disease. Here, we suggest that air drying capacity (ADC; an atmospheric state variable that controls the fate/evolution of the virus‐laden droplets) and ultraviolet radiation (UV) are probable environmental determinants in shaping the transmission of COVID‐19 at the seasonal time scale. These variables, unlike temperature and humidity, provide a physically based framework consistent with the apparent seasonal variability in COVID‐19 and prevalent across a broad range of climates (e.g., Germany and India). Since this disease is known to be influenced by the compounding effect of social, biological, and environmental determinants, this study does not claim that these environmental determinants exclusively shape the seasonality of COVID‐19. However, we argue that ADC and UV play a significant role in COVID‐19 dynamics at the seasonal scale. These findings could help guide the development of a sound adaptation strategy against the pandemic over the coming seasons.

Examining the factors influencing Pahang Mart portal using Technology acceptance model: the moderating effect of education level

The use of Pahang Mart portal greatly helps the people of Pahang to shop especially during the covid-19 season. However, if the system is not used optimally then waste will occur. Therefore, this study outlines the objectives that aim to identify the role of education level in moderating the relationship between perceived ease of use and intention to use Pahang Mart portal. The findings of the study have proven that performance expectancy has a significant relationship with the intention to use the Pahang Mart Portal application. However, the level of education does not play a significant role in simplifying the relationship between perceived ease of use and intention to use.

Measurement model for Pahang Portal Mart acceptance scale instrument

The use of Pahang Mart portal among the people of Pahang during the covid19 season is very encouraging. However, if the use of this portal is not complete, then the development of this portal will be a futile and detrimental project. A study on the acceptance of this portal is necessary and to ensure that this study has validity and reliability, the instrument needs to be proven in advance about its validity and reliability. Therefore, this study aims to determine the validity and reliability of the instrument that used to measure PahangMart portal acceptance. This study is a quantitative study using questionnaire instruments taken from previous researchers. The findings of the study prove that the questionnaire has a good level of validity and reliability.

Can SARS-CoV-2 Global Seasonality be Determined After One Year of Pandemic?

Supplemental Digital Content is available in the text.

Injury Rates in Major League Baseball During the 2020 COVID-19 Season.

Background:The 2020 Major League Baseball (MLB) season was drastically altered because of the COVID-19 pandemic. The changes included an extended layoff between March and July as well as a shortened preseason.Purpose/Hypothesis:To determine the incidence and epidemiology of MLB injuries in the abbreviated 2020 season compared with prior seasons. We hypothesized that there was an increase in the overall injury rate in the 2020 season compared with the 2018-2019 seasons and that it equally affected all body regions.Study Design:Descriptive epidemiology study.Methods:The MLB transactions database was queried to find players who had been placed on the injury list between 2018 and 2020. Injuries were categorized into upper extremity, lower extremity, spine/core, and other injuries. Incidence per 1000 athlete-exposures was calculated for the prior 2 seasons (2018-2019) and for the 2020 season separately. Incidence for each category was also calculated separately for pitchers and fielders. Incidence rate ratios (IRRs) and confidence intervals were used to compare injury rates in 2018-2019 versus 2020. The z test for proportions was used to determine significant differences between injury incidences.Results:In 2020, the overall incidence rate per 1000 athlete-exposures was almost twice the rate compared with the 2 seasons before COVID-19 (8.66 vs 5.13; IRR, 1.69 [95% CI, 1.53-1.87]; P < .001). Injury incidence increased similarly in 2020 for both pitchers (IRR, 1.68 [95% CI, 1.47-1.91]; P < .001) and fielders (IRR, 1.68 [95% CI, 1.45-1.96]; P < .001). Increases in injury incidence were seen in the upper extremity, spine/core, and other injury categories; however, the incidence of the lower extremity did not change significantly.Conclusion:There was a significant increase in injury incidence for both pitchers and fielders in 2020. Injury rates increased in anatomic zones of the upper extremity and spine/core but were not significantly changed in the lower extremity. The overall increase in injury rate suggests that irregular or insufficient sport-specific preparation prior to the start of the season placed athletes at a greater risk of injury when play resumed.

The role of seasonality in the spread of COVID-19 pandemic

It has been reported that the transmission of COVID-19 can be influenced by the variation of environmental factors due to the seasonal cycle. However, its underlying mechanism in the current and onward transmission pattern remains unclear owing to the limited data and difficulties in separating the impacts of social distancing. Understanding the role of seasonality in the spread of the COVID-19 pandemic is imperative in formulating public health interventions. Here, the seasonal signals of the COVID-19 time series are extracted using the EEMD method, and a modified Susceptible, Exposed, Infectious, Recovered (SEIR) model incorporated with seasonal factors is introduced to quantify its impact on the current COVID-19 pandemic. Seasonal signals decomposed via the EEMD method indicate that infectivity and mortality of SARS-CoV-2 are both higher in colder climates. The quantitative simulation shows that the cold season in the Southern Hemisphere countries caused a 59.71 ± 8.72% increase of the total infections, while the warm season in the Northern Hemisphere countries contributed to a 46.38 ± 29.10% reduction. COVID-19 seasonality is more pronounced at higher latitudes, where larger seasonal amplitudes of environmental indicators are observed. Seasonality alone is not sufficient to curb the virus transmission to an extent that intervention measures are no longer needed, but health care capacity should be scaled up in preparation for new surges in COVID-19 cases in the upcoming cold season. Our study highlights the necessity of considering seasonal factors when formulating intervention strategies.

Evidence and magnitude of the effects of meteorological changes on SARS-CoV-2 transmission.

Intensity and duration of the COVID-19 pandemic, and planning required to balance concerns of saving lives and avoiding economic collapse, could depend significantly on whether SARS-CoV-2 transmission is sensitive to seasonal changes. Hypothesis is that increasing temperature results in reduced SARS CoV-2 transmission and may help slow the increase of cases over time. Fifty representative Northern Hemisphere countries meeting specific criteria had sufficient COVID-19 case and meteorological data for analysis. Regression was used to find the relationship between the log of number of COVID-19 cases and temperature over time in 50 representative countries. To summarize the day-day variability, and reduce dimensionality, we selected a robust measure, Coefficient of Time (CT), for each location. The resulting regression coefficients were then used in a multivariable regression against meteorological, country-level and demographic covariates. Median minimum daily temperature showed the strongest correlation with the reciprocal of CT (which can be considered as a rate associated with doubling time) for confirmed cases (adjusted R2 = 0.610, p = 1.45E-06). A similar correlation was found using median daily dewpoint, which was highly colinear with temperature, and therefore was not used in the analysis. The correlation between minimum median temperature and the rate of increase of the log of confirmed cases was 47% and 45% greater than for cases of death and recovered cases of COVID-19, respectively. This suggests the primary influence of temperature is on SARS-CoV-2 transmission more than COVID-19 morbidity. Based on the correlation between temperature and the rate of increase in COVID-19, it can be estimated that, between the range of 30 to 100 degrees Fahrenheit, a one degree increase is associated with a 1% decrease-and a one degree decrease could be associated with a 3.7% increase-in the rate of increase of the log of daily confirmed cases. This model of the effect of decreasing temperatures can only be verified over time as the pandemic proceeds through colder months. The results suggest that boreal summer months are associated with slower rates of COVID-19 transmission, consistent with the behavior of a seasonal respiratory virus. Knowledge of COVID-19 seasonality could prove useful in local planning for phased reductions social interventions and help to prepare for the timing of possible pandemic resurgence during cooler months.

Effects of Environmental Factors on Severity and Mortality of COVID-19.

Background: Most respiratory viruses show pronounced seasonality, but for SARS-CoV-2, this still needs to be documented.Methods: We examined the disease progression of COVID-19 in 6,914 patients admitted to hospitals in Europe and China. In addition, we evaluated progress of disease symptoms in 37,187 individuals reporting symptoms into the COVID Symptom Study application.Findings: Meta-analysis of the mortality risk in seven European hospitals estimated odds ratios per 1-day increase in the admission date to be 0.981 (0.973–0.988, p < 0.001) and per increase in ambient temperature of 1°C to be 0.854 (0.773–0.944, p = 0.007). Statistically significant decreases of comparable magnitude in median hospital stay, probability of transfer to the intensive care unit, and need for mechanical ventilation were also observed in most, but not all hospitals. The analysis of individually reported symptoms of 37,187 individuals in the UK also showed the decrease in symptom duration and disease severity with time.Interpretation: Severity of COVID-19 in Europe decreased significantly between March and May and the seasonality of COVID-19 is the most likely explanation.