Seasonal Variation Analysis for Weekly Cases, Deaths, and Hospitalizations of COVID-19 in the United States.

Knowing the seasonality of COVID-19 helps decision-makers to take suitable interventions against the pandemic. In this study, we performed the Brown-Forsythe variance analysis on seasonal variations on different indicators based on the data on COVID-19 for the United States provided publicly by WHO. Our study finds that the seasonality of weekly cases and deaths of COVID-19 are strongly statistically supported by the data. The weekly total cases(/deaths) in winter are three to seven times(/two to three times) more than the other three single seasons. The ICU patients in winter and autumn are four to five times more than spring. The weekly hospital admissions in winter are four times more than spring. The mean of the positive rate in winter is five times more than spring. The findings of this research can be a reference in decision-making when taking interventions against the pandemic, such as taking stricter interventions in winter while considering less strict interventions in summer, etc.

Visits to Sexually Transmitted Infection Clinics in Italy from January 2016 to November 2021: A Multicenter, Retrospective Study.

There is no evidence of seasonal variation in visits to clinics dedicated to sexually transmitted infections (STIs) in Italy, nor of changes after the advent of the COVID-19 pandemic. An observational, retrospective, multicentric study was conducted to record and analyze all the visits to the STI clinics of the Dermatology Units of the University Hospitals of Ferrara and Bologna and of the Infectious Disease Unit of Ferrara, Italy, between January 2016 and November 2021. Overall, 11.733 visits were registered over a 70-month study period (63.7% males, mean age 34.5 ± 12.8 yrs). The mean number of monthly visits significantly decreased from the advent of the pandemic (136) compared to before (177). In the pre-pandemic period, visits to STI clinics increased in the autumn/winter months when compared to spring/summer, while the trend was the opposite in the pandemic period. Thus, during the pandemic, both an overall significant reduction in visits to STI clinics and a reversal in their seasonality were observed. These trends affected males and females equally. The marked decrease, mostly found in the pandemic winter months, can be linked to the "lockdown"/self-isolation ordinances and social distancing measures during the colder months, coinciding with the spread of the COVID-19 infection, which limited the opportunities for meeting and socializing.

The complex interplay between weather, social activity, and COVID-19 in the US.

Empirical studies on the impact of weather and policy interventions on Covid-19 infections have dedicated little attention to the mediation role of social activity. In this study, we combine mobile locations, weather, and COVID-19 data in a two-way fixed effects mediation model to estimate the impact of weather and policy interventions on the COVID-19 infection rate in the US before the availability of vaccines, disentangling their direct impact from the part of the effect that is mediated by the endogenous response of social activity. We show that, while temperature reduces viral infectiousness, it also increases the amount of time individuals spend out of home, which instead favours the spread of the virus. This second channel substantially attenuates the beneficial effect of temperature in curbing the spread of the virus, offsetting one-third of the potential seasonal fluctuations in the reproduction rate. The mediation role of social activity is particularly pronounced when viral incidence is low, and completely offsets the beneficial effect of temperature. Despite being significant predictors of social activity, wind speed and precipitation do not induce sufficient variation to affect infections. Our estimates also suggest that school closures and lockdowns are effective in reducing infections. We employ our estimates to quantify the seasonal variation in the reproduction rate stemming from weather seasonality in the US.

Early effects of COVID-19 on maternal and child health service disruption in Mozambique.

This article is part of the Research Topic 'Health Systems Recovery in the Context of COVID-19 and Protracted Conflict'. Introduction: After the World Health Organization declared COVID-19 a pandemic, more than 184 million cases and 4 million deaths had been recorded worldwide by July 2021. These are likely to be underestimates and do not distinguish between direct and indirect deaths resulting from disruptions in health care services. The purpose of our research was to assess the early impact of COVID-19 in 2020 and early 2021 on maternal and child healthcare service delivery at the district level in Mozambique using routine health information system data, and estimate associated excess maternal and child deaths. Methods: Using data from Mozambique's routine health information system (SISMA, Sistema de Informação em Saúde para Monitoria e Avaliação), we conducted a time-series analysis to assess changes in nine selected indicators representing the continuum of maternal and child health care service provision in 159 districts in Mozambique. The dataset was extracted as counts of services provided from January 2017 to March 2021. Descriptive statistics were used for district comparisons, and district-specific time-series plots were produced. We used absolute differences or ratios for comparisons between observed data and modeled predictions as a measure of the magnitude of loss in service provision. Mortality estimates were performed using the Lives Saved Tool (LiST). Results: All maternal and child health care service indicators that we assessed demonstrated service delivery disruptions (below 10% of the expected counts), with the number of new users of family planing and malaria treatment with Coartem (number of children under five treated) experiencing the largest disruptions. Immediate losses were observed in April 2020 for all indicators, with the exception of treatment of malaria with Coartem. The number of excess deaths estimated in 2020 due to loss of health service delivery were 11,337 (12.8%) children under five, 5,705 (11.3%) neonates, and 387 (7.6%) mothers. Conclusion: Findings from our study support existing research showing the negative impact of COVID-19 on maternal and child health services utilization in sub-Saharan Africa. This study offers subnational and granular estimates of service loss that can be useful for health system recovery planning. To our knowledge, it is the first study on the early impacts of COVID-19 on maternal and child health care service utilization conducted in an African Portuguese-speaking country.

Analytics of Epidemiological Data using Machine Learning Models

Epidemiological data is the data obtained based on disease, injury or environmental hazard occurrence using the previous data on the epidemic situation. We can use it for analysis and find the trends and patterns. We can use different machine learning models to create a platform that can be used for different time series data. We can rely on the properties of time series data like trends and seasonality and use this for future prediction. Acquiring the dataset is the first step in data preprocessing in machine learning. We have collected the dataset from ourWorldIndia website which is a real-life dataset of covid-19. This paper presents the idea of a dedicated machine learning model to forecast the future using epidemiological data. We have taken a data-set of covid-19 for the prediction of the number of daily cases infected by the coronavirus. Our machine learning model can be applied on the dataset of any country in the world. We have applied it on the dataset of India in the experimentation. Our goal behind this research paper is to give the ML model which can be easily used on any epidemiological data for prediction by analysing the seasonality.

Molecular Detection of Respiratory Syncytial Virus in Infants and Young Children by the Conventional Reverse Transcriptase Polymerase Chain Reaction

Background: At the peak of the viral season, World Health Organization ranked respiratory syncytial virus (RSV) as a major cause of acute respiratory infections in more than 60% of children and more than 80% of infants younger than one year. The current study is the first in the governorate of Was it to investigate respiratory syncytial virus subtypes. The objectives of the study were to estimate the frequency of respiratory syncytial virus in children <5 years old and to recognize some potential risk factors that might be associated with respiratory tract infections.Methodology: A cross sectional study with conventional reverse transcription polymerase chain reaction was performed on nasopharyngeal swabs from 158 pediatric patients. We compared the demographic and clinical characteristics of the patients aged 15 days to 60 months hospitalised with RTIs or seen at private clinics (cases, n = 158) and control children (n = 40) with non-respiratory symptoms during the respiratory season of 2021-2022. Pearson's chi-square (x2) model was applied, and P < 0.05 was considered significant.Results: RSV nucleic acid was detected in 15 (9.49%) of the 158 clinical specimens after amplification of the F gene. The identity of these amplified fragments was confirmed as human respiratory syncytial virus subtype B by sequencing. Except the clinical presentation there was no overall association between negative and positive cases while breast feeding and family history of the same condition when comparing the control and positive cases showed statistically significant.Conclusions: conventional PCR was successfully detected the subtype B of h RSV while it may not the appropriate PCR type for subtype A detecting or that the RSVB was the only subtype circulated in 2021-2022 winter.

Epidemiology and Risk Factor Analysis of Children with Bronchiolitis Admitted to the Intensive Care Unit at a Tertiary Care Center in Saudi Arabia.

Bronchiolitis is a leading cause of hospitalization worldwide for children aged ≤2 years. Few studies have compared general ward and pediatric intensive care unit (PICU) admissions, particularly in Saudi Arabia. This retrospective cohort study aimed to compare the demographic and clinical characteristics of children with bronchiolitis admitted to the general ward with those admitted to the PICU. Children (≤6 years) previously diagnosed with bronchiolitis and admitted to the PICU or general ward at a tertiary center in Saudi Arabia between May 2016 and May 2021 were included. Multiplex polymerase chain reaction was used to identify respiratory viruses. Of the 417 patients enrolled, 67 (16.06%) were admitted to the PICU. The PICU group was younger (median, 2 months; interquartile range [IQR], 1-5 months) vs. (6 months; IQR, 2.65-13.25 months). There was a dramatic reduction in bronchiolitis admissions during the COVID-19 pandemic. The most common causative virus was respiratory syncytial virus (RSV) (54.9%). In the multivariate regression analysis, hypoxia, hyperinflation on X-ray, and non-RSV bronchiolitis were independently associated with PICU admission. However, a higher chronological age and cough were protective. Children with Down syndrome, immunodeficiency, or neuromuscular disorders, and intermediate preterm infants (29-33 weeks of gestation) are at a high risk of PICU admission (adjusted odds ratio: 2.4, 7.1, 2.9, and 2.9; p = 0.037, 0.046, 0.033, and 0.029, respectively). Bronchiolitis is still one of the leading causes of PICU admission. Particular attention should be paid to preventive measures, especially in the post-COVID-19 era, targeting high-risk groups.

Predicting norovirus and rotavirus resurgence in the United States following the COVID-19 pandemic: a mathematical modelling study.

BACKGROUND: To reduce the burden from the COVID-19 pandemic in the United States, federal and state local governments implemented restrictions such as limitations on gatherings, restaurant dining, and travel, and recommended non-pharmaceutical interventions including physical distancing, mask-wearing, surface disinfection, and increased hand hygiene. Resulting behavioral changes impacted other infectious diseases including enteropathogens such as norovirus and rotavirus, which had fairly regular seasonal patterns prior to the COVID-19 pandemic. The study objective was to project future incidence of norovirus and rotavirus gastroenteritis as contacts resumed and other NPIs are relaxed. METHODS: We fitted compartmental mathematical models to pre-pandemic U.S. surveillance data (2012-2019) for norovirus and rotavirus using maximum likelihood estimation. Then, we projected incidence for 2022-2030 under scenarios where the number of contacts a person has per day varies from70%, 80%, 90%, and full resumption (100%) of pre-pandemic levels. RESULTS: We found that the population susceptibility to both viruses increased between March 2020 and November 2021. The 70-90% contact resumption scenarios led to lower incidence than observed pre-pandemic for both viruses. However, we found a greater than two-fold increase in community incidence relative to the pre-pandemic period under the 100% contact scenarios for both viruses. With rotavirus, for which population immunity is driven partially by vaccination, patterns settled into a new steady state quickly in 2022 under the 70-90% scenarios. For norovirus, for which immunity is relatively short-lasting and only acquired through infection, surged under the 100% contact scenario projection. CONCLUSIONS: These results, which quantify the consequences of population susceptibility build-up, can help public health agencies prepare for potential resurgence of enteric viruses.

COVID-19 through the lens of seasonal agriculture in South Asia

75% of the world's poor reside in rural areas where the local economy is tied to agriculture. We interpret new panel data on COVID-19 from Nepal and Bangladesh in relation to agricultural seasonality. Conditions in April–June 2020 were comparable to a typical lean season even though the pandemic arrived at harvest time. Income losses stem from both depressed local employment as well as lower migration and remittances. We also document indirect adverse health impacts on nutrition and mental health. Findings are specific to the nature of economic activity at harvest, and effective pandemic policy must evolve with the agricultural season. © 2023 Agricultural & Applied Economics Association.

Impact of the economic reform policy and COVID 19 on the seasonality of the most important Egyptian agricultural exports and imports

The research mainly aimed to study the impact of the economic reform policy and the Corona pandemic and seasonal factors on the prices of the most important Egyptian agricultural exports and imports. The most important results were the following: - By studying the trend analysis of the monthly average of the prices of the most important exported and imported commodities, it shows the real price increase over time per month for the exports of 17 commodities represented as "olive oil, dried fruits, Rumi cheese, aromatic oils and resins, dried onions, processed cheese, dried vegetables, white cheese, juices." Its foundations are oily seeds and fruits, onions and garlic, citrus fruits, preserved strawberries, frozen artichokes, processed potatoes, frozen vegetables, and potatoes. - Also found was that the economic reform policy had a statistically significant effect on the average real price of the exports of the 17 commodities under study, as well as the imports of meat, oils, sugar, beans, and wheat, in addition to the imports of the most important production requirements studied, such as seeds, pesticides, disinfectants, and fertilizers. that during the study period. - By studying the impact of the COVID-19 crisis on the real monthly prices of exports and imports of the commodities under study, it was found that the average monthly price decreased in real prices for all commodities under study, except for oils and aromatic resins, but the statistical significance of the rates of decrease during the study period did not prove.

EVALUATION OF AIR TRAFFIC IN THE CONTEXT OF THE COVID-19 PANDEMIC

The Covid-19 pandemic unexpectedly shook the entire global economy, causing it to destabilize over a long period of time. One of the sectors that was particularly hit hard was air traffic, and the changes that have taken place in it have been unmatched by any other crisis in history. The purpose of this article was to identify the time series describing the number of airline flights in Poland in the context of the Covid-19 pandemic. The article first presents selected statistics and indicators showing the situation of the global and domestic aviation market during the pandemic. Then, based on the data on the number of flights in Poland, the identification of the time series describing the number of flights by airlines was made. The discrete wavelet transformation (DWT) was used to determine the trend, while for periodicity verification, first statistical tests (Kruskal-Wallis test and Friedman test) and then spectral analysis were used. The confirmation of the existence of weekly seasonality allowed for the identification of the studied series as the sum of the previously determined trend and the seasonal component, as the mean value from the observations on a given day of the week. The proposed model was compared with the 7-order moving average model, as one of the most popular in the literature. As the obtained results showed, the model developed by the authors was better at identifying the studied series than the moving average. The errors were significantly lower, which made the presented solution more effective. This confirmed the validity of using wavelet analysis in the case of irregular behaviour of time series, and also showed that both spectral analysis and statistical tests (Kruskal-Walis and Fridman) proved successful in identifying the seasonal factor in the time series. The method used allowed for a satisfactory identification of the model for empirical data, however, it should be emphasized that the aviation services market is influenced by many variables and the forecasts and scenarios created should be updated and modified on an ongoing basis. © 2022 Warsaw University of Technology. All rights reserved.

Impact of the COVID-19 pandemic on the seasonality of respiratory syncytial viral infection.

The article presents an overview of current trends in the epidemiology of respiratory syncytial viral (RSV) infection, including its seasonality, under the impact of the COVID-19 pandemic, both according to world literature and taking into account monitoring epidemiological studies conducted in the Russian Federation. A detailed description of the dynamics of RSV detection in the period 2020-2021 and the beginning of 2022 in Russia according to the results of the all-Russian epidemiological monitoring is given. Epidemiological studies in different regions of the world, including Russia, have revealed the absence of seasonal rises in the incidence of RSV infection, characteristic of previous years, in 2020 and winter-spring in 2021 under the influence of the COVID-19 pandemic. In 2021-2022, a sharp increase in the incidence and hospitalization of children was noted against the backdrop of a decrease in cases of a new coronavirus infection in all countries of the world, while the start time and duration of respiratory syncytial virus infection, typical for the prepandemic period, changed. Our previous studies have shown that in different years and in different regions of Russia, the start and end times of the epidemiological season may also not coincide, which makes it difficult to predict seasonal peaks in incidence, their duration and severity only on the basis of previously obtained data. This makes it expedient to extend the terms of passive specific prophylaxis with palivizumab for a year if there are indications for its use, including taking into account the data of epidemiological monitoring conducted in the Russian Federation.Copyright © 2022 Authors. All rights reserved.

Impact of the COVID-19 pandemic on the seasonality of respiratory syncytial viral infection

The article presents an overview of current trends in the epidemiology of respiratory syncytial viral (RSV) infection, including its seasonality, under the impact of the COVID-19 pandemic, both according to world literature and taking into account monitoring epidemiological studies conducted in the Russian Federation. A detailed description of the dynamics of RSV detection in the period 2020-2021 and the beginning of 2022 in Russia according to the results of the all-Russian epidemiological monitoring is given. Epidemiological studies in different regions of the world, including Russia, have revealed the absence of seasonal rises in the incidence of RSV infection, characteristic of previous years, in 2020 and winter-spring in 2021 under the influence of the COVID-19 pandemic. In 2021-2022, a sharp increase in the incidence and hospitalization of children was noted against the backdrop of a decrease in cases of a new coronavirus infection in all countries of the world, while the start time and duration of respiratory syncytial virus infection, typical for the prepandemic period, changed. Our previous studies have shown that in different years and in different regions of Russia, the start and end times of the epidemiological season may also not coincide, which makes it difficult to predict seasonal peaks in incidence, their duration and severity only on the basis of previously obtained data. This makes it expedient to extend the terms of passive specific prophylaxis with palivizumab for a year if there are indications for its use, including taking into account the data of epidemiological monitoring conducted in the Russian Federation. © 2022 Authors. All rights reserved.

Impact of the COVID-19 pandemic on the seasonality of respiratory syncytial viral infection.

The article presents an overview of current trends in the epidemiology of respiratory syncytial viral (RSV) infection, including its seasonality, under the impact of the COVID-19 pandemic, both according to world literature and taking into account monitoring epidemiological studies conducted in the Russian Federation. A detailed description of the dynamics of RSV detection in the period 2020-2021 and the beginning of 2022 in Russia according to the results of the all-Russian epidemiological monitoring is given. Epidemiological studies in different regions of the world, including Russia, have revealed the absence of seasonal rises in the incidence of RSV infection, characteristic of previous years, in 2020 and winter-spring in 2021 under the influence of the COVID-19 pandemic. In 2021-2022, a sharp increase in the incidence and hospitalization of children was noted against the backdrop of a decrease in cases of a new coronavirus infection in all countries of the world, while the start time and duration of respiratory syncytial virus infection, typical for the prepandemic period, changed. Our previous studies have shown that in different years and in different regions of Russia, the start and end times of the epidemiological season may also not coincide, which makes it difficult to predict seasonal peaks in incidence, their duration and severity only on the basis of previously obtained data. This makes it expedient to extend the terms of passive specific prophylaxis with palivizumab for a year if there are indications for its use, including taking into account the data of epidemiological monitoring conducted in the Russian Federation.Copyright © 2022 Authors. All rights reserved.

Surveillance of respiratory viruses infections in sentinel hospitals of Guangming district, Shenzhen, between 2018 and 2021

OBJECTIVE: To investigate the prevalence of respiratory tract viruses infections in sentinel hospitals of Guangming District, Shenzhen, from 2018 to 2021. METHODS: A total of 1 183 influenza-like patients who were treated in University of Chinese Academy of Sciences Shenzhen Hospital(Guangming District) from Jan 2018 to Dec 2021 were recruited as the research subjects. The respiratory viruses that were isolated from throat swab specimens were detected by real-time fluorescent quantitative PCR, and the prevalence of the infections was observed. RESULTS: Among the throat swab specimens that were collected from the 1 183 influenza-like patients, 45.48%(538/1183) were tested positive for respiratory viruses. Among the 538 positive samples, 533 were single infection, and 5 were mixed infection;the patients with influenza virus infection accounted for 77.51%(417 cases), higher than the patients with infections of other viruses [adenovirus infection(6.51%), respiratory syncytial virus infection(1.30%), human metapneumovirus infection(1.67%), rhinovirus infection(6.88%), coronavirus infection(1.86%), parainfluenza virus infection(3.16%), boca virus infection(0.19%), P<0.05]. The incidence of respiratory viruses infections was higher in winter than in spring, summer and autumn(P<0.05), the proportion of the influenza virus was higher than that of other viruses in winter(P<0.05). The population aged between 26 and 40 years old was dominant among the patients with influenza virus infection, and the infection rate of the age group was higher than that of other age groups(P<0.05). The population aged between 26 and 40 years old was dominant among the patients with coronavirus infection, while the population aged less than 15 years old was dominant among the patients with infections of other respiratory viruses;the patients aged less than 15 years accounted for 59.46%(22 cases) among the patients with rhinovirus infection;the patients aged less than 5 years old accounted for 42.86%(15 cases) among the patients with adenovirus infection. There was no significant difference in the proportion of the patients with respiratory viruses infection between genders. CONCLUSION: The influenza virus is dominant among the viruses causing the respiratory tract infection, which is prevalent in winter. The incidence of respiratory tract infections is relatively high among the patients aged between 26 and 40 years old but is not associated with the gender.

Epidemiological investigation of bovine viral diarrhea virus infection in swinery

From 2017 to 2020, 1 078 piglet diarrhea samples were collected from 6 pig farms in different districts of Shanghai. Multiple RT-PCR method was used for detection and analysis to study the infection status of bovine viral diarrhea virus (BVDV) in swinery in Shanghai. The results showed that the overall detection rate of BVDV in swinery in Shanghai was 7.14% (77/1 078), and showed an increasing trend year by year. The mixed infection rate of BVDV and other diarrhea pathogens was high, with the highest dual infection rate (65%, 26/40), mainly BVDV/PASTV (61.54%, 16/26). On this basis, the triple infection rate was 25% (10/40), mainly BVDV/PAStV/PKoV (40%, 4/10) infection mode;The quadruple infection rate was 10% (4/40), which was dominated by BVDV/PAStV/PEDV/PSV (50%, 2/4) infection. The BVDV prevalence in swinery was seasonal, and the prevalence in spring (10.36%) and autumn (13.59%) was higher than that in summer (6.8%) and winter (2.66%). The positive rate of BVDV in different pig farms was significantly different by 0-24.07%. In view of the detection rate of diarrhea virus dominated by PEDV in pig farm 2 had been high in recent years, this study further monitored the infection of BVDV in this pig farm, and found that the detection rate of BVDV in this pig farm was increasing year by year from 2017 to 2019, with the highest detection rate in 2019 (8.61%, 42/488);The mixed infection of BVDV and other diarrhea pathogens was also serious, with the dual infection rate of 57.58% (19/32), triple infection rate of 21.21% (7/32), quadruple infection rate of 21.21% (7/32), respectively. This study enriched the epidemic data of BVDV in swinery in Shanghai, and could provide reference for the prevention and control of pig epidemics.

Statistical analysis of the impacts of COVID-19 pandemic on the small and large-scale tourism sectors in developing countries.

The worldwide COVID-19 pandemic has affected the tourism sector by closing borders, reducing both the transportation of tourists and tourist demand. Due to the country-wide lockdown, most activities in the hotel, motel, restaurant, and transportation sectors have been postponed. Consequently, the article investigates four research issues by examining the consequences of global tourism in the private sector before and after COVID-19. As an analytical method, the article suggested qualitative research methodologies to collect information from tourism employees. The opinions of the respondents were gathered through online emails in the questionnaire survey. Further, the article considers people's future desire for specific tourism destinations based on visitor arrivals. Forecasting tourist demand is an essential component of good and efficient tourism management. Consequently, the article proposes an attention-based long short-term memory model for exact demand forecasting. The experimental findings reveal that the model's minimal prediction error accuracy is 0.45%, which indicates that it has a more robust prediction effect, a faster convergence rate, and a greater prediction accuracy. Seasonality has emerged as one of the most distinguishing and defining characteristics of the global tourist business. Accordingly, the article mandated to compare the seasonal and non-seasonal effects of the tourist sector throughout the years 2020-2021. Moreover, Governments must analyse the crises' long-term consequences and, as a result, define the components that constitute government advantages supplied to the tourist sector during the pandemic era. As a result, many governmental policies, especially those about social welfare, may perceive a fresh start during the post-pandemic period, respectively.

Seasonality, mass vaccination and critical policy evaluation on global exit strategy of COVID-19 crisis.

There is a strong coordinated effort by vaccination groups all over the world to put an end to the current crisis of COVID-19. Now sufficient data are available to analyse and compare some results to explore the aftereffects of vaccination. Some influence variables on transmissions of the disease were discussed e.g., mass vaccination, lockdown and seasonality. Most studies covered here are up to the beginning of July 2022, while some analyses focused on the earlier period of mass vaccination. Well established, simple statistical techniques to evaluate results were presented those used open data sources of authoritative bodies. Some comparisons between vaccinated vs. unvaccinated were also discussed based on data from UK Government Health Security Agency (UHSA). In terms of mass vaccination, adverse reactions after vaccination received attention, as health and safety issues of the general public are of prime importance. Apart from direct side effects, the secondary effect of mass vaccination needs attention too. After the initiation of the vaccination programme, almost all countries experienced a sudden surge in transmission and most countries had to impose strict lockdown measures. Many countries, with a low prevalence of disease, suddenly showed a steep jump and some countries even followed a synchronized pattern between the rate of transmissions and the variation of vaccine doses. Time series analyses and bar diagram presentations were able to capture those features. In that context, fast mutation of the virus and new variants after mass vaccination and possible mechanisms/consequences were also attended. To understand the effect of seasonality, similarities between COVID-19 and the seasonal Flu are discussed for Europe and US to gain useful insight. Using time series analyses and spatial plots of regional temperature composites we showed, like Flu, seasonality played a dominant role in transmissions of COVID-19 in the Europe. Regulations of vaccine dose and policy implication were explored too. From 22nd December 2021, global vaccine doses were reduced substantially, which followed a dramatic reduction in cases and thereafter deaths with around one month's lag between each. As strong dependency on seasonality is noticed in certain countries and observing that regulation of vaccine doses has roles in modulating the transmission with certain lags, globally as well as regionally, our results have policy implications for the management of COVID. Debating, questioning and criticism are always the foundation of great science and the major pillars of its progress. Following that objective, it is an effort to explore pragmatically, supported by scientific analyses, areas relating to the effectiveness of the COVID-19 vaccine and the exit strategy via the pathway of vaccination.

Disentangling the rhythms of human activity in the built environment for airborne transmission risk: An analysis of large-scale mobility data.

Background: Since the outset of the COVID-19 pandemic, substantial public attention has focused on the role of seasonality in impacting transmission. Misconceptions have relied on seasonal mediation of respiratory diseases driven solely by environmental variables. However, seasonality is expected to be driven by host social behavior, particularly in highly susceptible populations. A key gap in understanding the role of social behavior in respiratory disease seasonality is our incomplete understanding of the seasonality of indoor human activity. Methods: We leverage a novel data stream on human mobility to characterize activity in indoor versus outdoor environments in the United States. We use an observational mobile app-based location dataset encompassing over 5 million locations nationally. We classify locations as primarily indoor (e.g. stores, offices) or outdoor (e.g. playgrounds, farmers markets), disentangling location-specific visits into indoor and outdoor, to arrive at a fine-scale measure of indoor to outdoor human activity across time and space. Results: We find the proportion of indoor to outdoor activity during a baseline year is seasonal, peaking in winter months. The measure displays a latitudinal gradient with stronger seasonality at northern latitudes and an additional summer peak in southern latitudes. We statistically fit this baseline indoor-outdoor activity measure to inform the incorporation of this complex empirical pattern into infectious disease dynamic models. However, we find that the disruption of the COVID-19 pandemic caused these patterns to shift significantly from baseline and the empirical patterns are necessary to predict spatiotemporal heterogeneity in disease dynamics. Conclusions: Our work empirically characterizes, for the first time, the seasonality of human social behavior at a large scale with a high spatiotemporal resolutio and provides a parsimonious parameterization of seasonal behavior that can be included in infectious disease dynamics models. We provide critical evidence and methods necessary to inform the public health of seasonal and pandemic respiratory pathogens and improve our understanding of the relationship between the physical environment and infection risk in the context of global change. Funding: Research reported in this publication was supported by the National Institute of General Medical Sciences of the National Institutes of Health under award number R01GM123007.

Defining the South African Acute Respiratory Infectious Disease Season.

The acute respiratory infectious disease season, or colloquially the "flu season", is defined as the annually recurring period characterized by the prevalence of an outbreak of acute respiratory infectious diseases. It has been widely agreed that this season spans the winter period globally, but the precise timing or intensity of the season onset in South Africa is not well defined. This limits the efficacy of the public health sector to vaccinate for influenza timeously and for health facilities to synchronize efficiently for an increase in cases. This study explores the statistical intensity thresholds in defining this season to determine the start and finish date of the acute respiratory infectious disease season in South Africa. Two sets of data were utilized: public-sector hospitalization data that included laboratory-tested RSV and influenza cases and private-sector medical insurance claims under ICD 10 codes J111, J118, J110, and J00. Using the intensity threshold methodology proposed by the US CDC in 2017, various thresholds were tested for alignment with the nineteen-week flu season as proposed by the South African NICD. This resulted in varying thresholds for each province. The respiratory disease season commences in May and ends in September. These findings were seen in hospitalization cases and medical insurance claim cases, particularly with influenza-positive cases in Baragwanath hospital for the year 2019. These statistically determined intensity thresholds and timing of the acute respiratory infectious disease season allow for improved surveillance and preparedness among the public and private healthcare.