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The COVID-19 disease was first identified in Wuhan, China, in December 2019, having since spread rapidly across the world. The infection and mortality rates of the disease have forced governments to implement a wave of public health measures. Depending on the context, these range from the implementation of simple hygienic rules to measures such as social distancing or lockdowns that cause major disruptions in citizens’ daily lives. The success of these crucial public health measures rests on the public's willingness to comply. However, individual differences in following the official public health recommendations for stopping the spread of COVID-19 have not yet to our knowledge been assessed. This study aims to fill this gap by assessing the sociodemographic and psychological correlates of implementing public health recommendations that aim to halt the COVID-19 pandemic. We investigate these associations in the context of France, one of the countries that has been most severely affected by the pandemic, and which ended up under a nationwide lockdown on March 17. In the next sections we describe our theoretical expectations over the associations between sociodemographics, personality, ideology, and emotions with abiding by the COVID-19 public health measures. We then test these hypotheses using data from the French Election Study.
The aim of this study was to analyze the impact coronavirus disease 2019 (COVID-19) had in Argentina during its initial stage, identify the measures taken to try to mitigate its impact, and briefly compare it with the influenza A H1N1 pandemic in 2009. This is a descriptive study. Pandemics constitute a serious problem to global health with a major impact on the affected countries’ populations. The recent COVID-19 outbreak represents one of the most important viral pandemics lately. It reached Argentina 64 days after the first case was identified in China. Since then, several measures were taken by the Argentinian government to try to mitigate its impact in this initial stage. An updated report of the current situation and its management in different countries is of vital importance regarding global health issues and may serve for feedback and decision-making.
In an effort to support the mental health of Albertans during the coronavirus disease 2019 (COVID-19) pandemic, Alberta Health Services launched a supportive text message (Text4Mood) program on March 23, 2020. The program was simultaneously approved for funding by the 6 regional health foundations and launched within 1 week of conception. Residents of Alberta can subscribe to the program by texting “COVID19HOPE” to a sort code number. Each subscriber receives free daily supportive text messages, for 3 months, crafted by a team of clinical psychologists, psychiatrists, mental health therapist, and mental health service users. Within 1 week of the launch of Text4Hope, 32 805 subscribers had signed up to the program, and there have been expressions of interests from other jurisdictions to implement a similar program to support the mental health of those in quarantine, isolation, or lockdown.
The objective of this paper is to prepare the government and citizens of India to take or implement the control measures proactively to reduce the impact of coronavirus disease 2019 (COVID-19).
Method:
In this work, the COVID-19 outbreak in India has been predicted based on the pattern of China using a machine learning approach. The model is built to predict the number of confirmed cases, recovered cases, and death cases based on the data available between January 22, 2020, and April 3, 2020. The time series forecasting method is used for prediction models.
Results:
The COVID-19 effects are predicted to be at peak between the third and fourth weeks of April 2020 in India. This outbreak is predicted to be controlled around the end of May 2020. The total number of predicted confirmed cases of COVID-19 might reach around 68 978, and the number of deaths due to COVID-19 are predicted to be 1557 around April 25, 2020, in India. If this outbreak is not controlled by the end of May 2020, then India will face a severe shortage of hospitals, and it will make this outbreak even worse.
Conclusion:
The COVID-19 pandemic may be controlled if the Government of India takes proactive steps to aggressively implement a lockdown in the country and extend it further. This presented epidemiological model is an effort to predict the future forecast of COVID-19 spread, based on the present scenario, so that the government can frame policy decisions, and necessary actions can be initiated.
The world economy is sliding yet into another recession (having arguably barely recovered from the previous economic downturn) due to the worldwide pressures and tensions created by the COVID-19 pandemic.1 With most countries in the world under lockdown (or in similar situations), almost all food is now consumed in the household. Arguably, agricultural producers and the retail industry appear to be the best placed to weather the storm in order to respond to such a change in demand. However, this is overly simplistic. Recent news of empty shelves in supermarkets whilst dairy farmers have been forced to pour milk down the drain have gone viral.