Covid gif

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Covid gif

High cholesterol causes 4. Poor diet is a leading risk factor for CVD, diabetes and obesity. Hypertension is the number one risk factor for death globally. One of the most important public health problems facing the world today. There are immediate health benefits to quitting tobacco. Please help to deliver the best web experience by completing a short questionnaire Takes 4 minutes to complete. Log into My WHF. South-East Asia. Western Pacific. Chagas Disease Chagas can cause irreversible damage to the heart. Cholesterol High cholesterol causes 4.

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Siouxsie Wiles is a microbiologist and award-winning science communicator based at the University of Auckland in Aotearoa New Zealand. Her academic research focuses on how the infectiousness of bacteria changes over time and developing new antibiotics. During the early days of the Covid pandemic, she worked with cartoonist Toby Morris to create simple graphic messages that could get public health information out to the general public quickly and effectively, reassuring and informing people throughout Aotearoa New Zealand and around the world. The teal and orange GIF toggled between two scenarios. It was inspired by a tweet I saw in late February Dr Drew Harris drewaharris , a health policy and population health educator, tweeted a modified version of a CDC graphic showing how protective measures could be used to slow daily cases of a disease. Harris had added a very important line to the CDC graphic: a measure of healthcare capacity. Our individual attitudes and actions mattered. We could all help flatten the curve. Within days the GIF had gained millions of impressions on Twitter and had spread around the world.

Covid gif

The Cumulative Cases animation shows the total number of cases reported in each country at each point in time, regardless of how many people have recovered. Visualizing cumulative cases demonstrates the overall toll of coronavirus on a country over time. The New Cases animation uses a 5-day moving average, calculated for each day by averaging the values of that day, the two days before, and the two next days. This approach helps prevent events like a change in reporting methods or data variability from skewing the case count. Visualizing new cases demonstrates where the coronavirus actively spread during the past one to two weeks.

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