Practical Indicators for Risk of Airborne Transmission in Shared Indoor Environments and Their Application to COVID-19 Outbreaks.

Some infectious diseases, including COVID-19, can undergo airborne transmission. This may happen at close proximity, but as time indoors increases, infections can occur in shared room air despite distancing. We propose two indicators of infection risk for this situation, that is, relative risk parameter (Hr) and risk parameter (H). They combine the key factors that control airborne disease transmission indoors: virus-containing aerosol generation rate, breathing flow rate, masking and its quality, ventilation and aerosol-removal rates, number of occupants, and duration of exposure. COVID-19 outbreaks show a clear trend that is consistent with airborne infection and enable recommendations to minimize transmission risk. Transmission in typical prepandemic indoor spaces is highly sensitive to mitigation efforts. Previous outbreaks of measles, influenza, and tuberculosis were also assessed. Measles outbreaks occur at much lower risk parameter values than COVID-19, while tuberculosis outbreaks are observed at higher risk parameter values. Because both diseases are accepted as airborne, the fact that COVID-19 is less contagious than measles does not rule out airborne transmission. It is important that future outbreak reports include information on masking, ventilation and aerosol-removal rates, number of occupants, and duration of exposure, to investigate airborne transmission.

Statistical Analysis of Novel COVID-19 Based on Real-Time Data and Future Epidemics

The buzzword in the health sector globally was COVID-19 alias coronavirus. Present all over the world, the virus spread rapidly from one person to another. The outbreak was first reported in Wuhan, China, in December 2019, exponentially spreading to the entire China. In the past months, COVID-19 becomes an outbreak throughout the world. The impact of this new virus brought horror to several countries as cities are quarantined and locked down and hospitals are overcrowded. A high infectious ailment that compromises the worldwide world, part of things isn’t completely comprehended. Our study focuses on COVID-19-infected cases in India. Sickness classification is one of the significant and more time-consuming tasks in medical diagnosis system. In India, COVID-19 cases are slowly increasing day by day. Compared to advanced countries, the spread is under control. Here, we have customized our prepared dataset based on the government of India’s data provided by ICMR. Statistical analysis on COVID-19-infected, death and recovered cases among India’s various states is based on the real-time data. To forecast the coronavirus’s epidemic peak, what might help us act appropriately to reduce the epidemic risk? We used compartmental model in epidemiology, the SEIR method, to forecast the number of confirmed cases based on the current scenario and population. Further, we used machine learning methods such as ARIMA and SEIR models to forecast India’s confirmed cases in the coming days and to start to forecast the decrease of infected cases by the end of the year 2020. Our study can predict the infected patients based on symptoms using ARIMA and SEIR model. At the last comparison of the cases based on prediction and with lockdown cases. Finally, we suggested preventive measures to minimize COVID-19 infections. This work expects to predict and forecast COVID-19 cases, deaths and recoveries through predictive modelling. The model helps to interpret public sentiment patterns on scattering related health information and assess the political and financial impact of the spread of the infection. Methods: Real-time data query has been visualized in this work. The queried data is used for susceptible-exposed-infectious-recovered (SEIR) predictive modelling and forecasting the number of cases and infected using autoregressive integrated moving average (ARIMA). We utilized SEIR model and ARIMA model to forecast COVID-19 outbreak within India based on daily observations. Findings: At the time of writing this book chapter, the number of confirmed cases is expected to exceed 473,000 and reach the peak of this outbreak before 30 June 2020. This outbreak is assumed to peak in late August 2020 and will start to drop around early September 2020. © 2022, Springer Nature Switzerland AG.

Postexposure psychological sequelae in frontline health workers to COVID-19 in Andhra Pradesh, India.

INTRODUCTION: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 has engulfed the globe since December 2019. Healthcare workers remain at the forefront of this battle, and like prior pandemics face mental health challenges along with physical risks. We aimed to study the perceived stress and possible posttraumatic stress in the frontline workers exposed to active COVID-19 duties in the state of Andhra Pradesh, India. METHODOLOGY: A special voluntary, anonymous, survey-based Google questionnaire was designed with mandatory consent form and queries to clarify inclusion exclusion criteria. Tools included valid, reliable self-administered scales, namely General Health Questionnaire 12, Perceived Stress Scale and Impact of Events Scales-Revised. A purposive sampling method was adopted, by posting the survey questionnaire on WhatsApp groups of doctors, interns, and nurses working on active COVID-19 duty in Andhra Pradesh. RESULTS: About 69.7% of the frontline workers recorded higher perceived stress and definitive posttraumatic stress disorder (PTSD) was found in 34.8%, with psychological distress recorded in 53%. CONCLUSION: The higher levels of perceived stress discovered in the vast majority with definitive PTSD features in a third of the sample indicates the need for provision of mental health support proactively among frontline workers on active COVID-19 duty.

Dismantling myths on the airborne transmission of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2).

The coronavirus disease 2019 (COVID-19) pandemic has caused untold disruption throughout the world. Understanding the mechanisms for transmission of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is key to preventing further spread, but there is confusion over the meaning of 'airborne' whenever transmission is discussed. Scientific ambivalence originates from evidence published many years ago which has generated mythological beliefs that obscure current thinking. This article collates and explores some of the most commonly held dogmas on airborne transmission in order to stimulate revision of the science in the light of current evidence. Six 'myths' are presented, explained and ultimately refuted on the basis of recently published papers and expert opinion from previous work related to similar viruses. There is little doubt that SARS-CoV-2 is transmitted via a range of airborne particle sizes subject to all the usual ventilation parameters and human behaviour. Experts from specialties encompassing aerosol studies, ventilation, engineering, physics, virology and clinical medicine have joined together to produce this review to consolidate the evidence for airborne transmission mechanisms, and offer justification for modern strategies for prevention and control of COVID-19 in health care and the community.

Agriculture during the COVID-19 pandemic: problems and prospects

The current COVID-19 pandemic sweeping across the globe is expected to have a disastrous impact on the world economy. Indian economy is also expected to face severe headwinds. Indian agriculture remains a bright spot though. The real gross domestic product (GDP) from agriculture & allied activities is expected to maintain a robust growth rate of 3% in 2020-21, which in turn can help the overall growth in GDP. The factors on supply side appear to be largely adequate with robust foodgrain production and sufficient stocks. The prices of most of the food commodities have shown a decline in the month of March both at wholesale and retail levels. However, major problem could arise on the demand side due to disruption of livelihoods during the lockdown period leading to lower incomes for farmers, agricultural labourers and seasonal migrants. This negative impact on rural income is likely to derail the economy, which was already reeling with demand contraction even before the crisis. Hence, several safety nets, such as direct cash payments, free distribution of grains, etc., are needed. These safety nets are needed for at least six months. Immediately after the lockdown period, the activities in agricultural market are likely to increase. The measures of social distancing and hygiene need to be strictly enforced at this time. The supply of inputs, labour and machinery for the upcoming kharif season needs to be ensured with adequate health safeguards. In the wake of fears of a second wave of COVID-19 around November, the recent initiative of selling and transporting directly from the warehouses and FPOs, without passing through the APMC mandies, needs to be strengthened. Also, a robust system of direct payments and grain distribution to the vulnerable sections needs to be continued. Given the satisfactory state of domestic food supplies, restrictions on exports need to be avoided as it could hamper our global food markets.