Using a rich individual level dataset from six countries, we examine the association between job loss and mental wellbeing loss during the first phase of the COVID-19 pandemic. We consider four indicators of mental health status based on their severity, viz. anxiety, insomnia, boredom, and loneliness. We draw our conclusions based on two groups of countries that differ by the timing of their peak infections count. Using a logit model and controlling for endogeneity, we find that the people who lost their jobs due to the pandemic are more likely to suffer from mental wellbeing loss, especially insomnia and loneliness. Additionally, people with financial liabilities, such as housing mortgages, are among the mentally vulnerable groups to anxiety. Women, urban residences, youth, low-income groups, and tobacco users are more prone to mental wellbeing loss. The findings from this research have significant policy implications on infectious disease control measures and mental health status due to lockdowns and social distancing.

Australia recorded 20553 Coronavirus Deaths since the epidemic began, according to the World Health Organization (WHO). In addition, Australia reported 11299954 Coronavirus Cases. This dataset includes a chart with historical data for Australia Coronavirus Deaths.

This dataset corresponds to paper titled "A Mathematical Model for COVID-19 Considering Waning Immunity, Vaccination and Control Measures". In this work we define a modified SEIR model that accounts for the spread of infection during the latent period, infections from asymptomatic or pauci-symptomatic infected individuals, potential loss of acquired immunity, people’s increasing awareness of social distancing and the use of vaccination as well as non-pharmaceutical interventions like social confinement. We estimate model parameters in three different scenarios - in Italy, where there is a growing number of cases and re-emergence of the epidemic, in India, where there are significant number of cases post confinement period and in Victoria, Australia where a re-emergence has been controlled with severe social confinement program. Our result shows the benefit of long term confinement of 50% or above population and extensive testing. With respect to loss of acquired immunity, our model suggests higher impact for Italy. We also show that a reasonably effective vaccine with mass vaccination program can be successful in significantly controlling the size of infected population. We show that for India, a reduction in contact rate by 50% compared to a reduction of 10% in the current stage can reduce death from 0.0268% to 0.0141% of population. Similarly, for Italy we show that reducing contact rate by half can reduce a potential peak infection of 15% population to less than 1.5% of population, and potential deaths from 0.48% to 0.04%. With respect to vaccination, we show that even a 75% efficient vaccine administered to 50% population can reduce the peak number of infected population by nearly 50% in Italy. Similarly, for India, a 0.056% of population would die without vaccination, while 93.75% efficient vaccine given to 30\% population would bring this down to 0.036% of population, and 93.75% efficient vaccine given to 70% population would bring this down to 0.034%.

This dataset corresponds to paper titled "COVID-19: Risks of Re-emergence, Re-infection, and Control Measures -- A Long Term Modeling Study". In this work we define a modified SEIR model that accounts for the spread of infection during the latent period, infections from asymptomatic or pauci-symptomatic infected individuals, potential loss of acquired immunity, people’s increasing awareness of social distancing and the use of vaccination as well as non-pharmaceutical interventions like social confinement. We estimate model parameters in three different scenarios - in Italy, where there is a growing number of cases and re-emergence of the epidemic, in India, where there are significant number of cases post confinement period and in Victoria, Australia where a re-emergence has been controlled with severe social confinement program. Our result shows the benefit of long term confinement of 50% or above population and extensive testing. With respect to loss of acquired immunity, our model suggests higher impact for Italy. We also show that a reasonably effective vaccine with mass vaccination program can be successful in significantly controlling the size of infected population. We show that for India, a reduction in contact rate by 50% compared to a reduction of 10% in the current stage can reduce death from 0.0268% to 0.0141% of population. Similarly, for Italy we show that reducing contact rate by half can reduce a potential peak infection of 15% population to less than 1.5% of population, and potential deaths from 0.48% to 0.04%. With respect to vaccination, we show that even a 75% efficient vaccine administered to 50% population can reduce the peak number of infected population by nearly 50% in Italy. Similarly, for India, a 0.056% of population would die without vaccination, while 93.75% efficient vaccine given to 30\% population would bring this down to 0.036% of population, and 93.75% efficient vaccine given to 70% population would bring this down to 0.034%.