COVID-19 and other examples

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Giving COVID-19 as an example might be a bit dicey because it's recent enough not all the facts about it are entirely certain. It also seems it's not useful unless it has a visual component. Is Template:2019–20 coronavirus outbreak data/China medical cases (confirmed) reasonable? The text sounds like it's focusing on the very early days, which this graph does not show well. It would be good to have at least three charts, showing clear cases of "point", "continuous", and "propagation" patterns; it sounds like COVID-19 is a mix of two. -- Beland (talk) 17:15, 20 February 2020 (UTC)Reply

Proposed merge of Flatten the curve into Epidemic curve

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"Flattening the curve" is a concept entirely related to epidemic curves, so there's no need for a separate article just for the label. These are both small pages, so it'll be better to build them up together. {{u|Sdkb}}talk 07:06, 8 April 2020 (UTC)Reply

Hello Sdkb. I'am skeptical on "they are entirely related". I see Epidemic curve as epidemiology alone, with technicalities related to its scientific measure and representation.
Flatten the curve and raise the line have their center on health management, public policies, logistic issues, the concept is from an other field and could have its own development and article. Like disaster (earthquake, hurricane) and disaster management.
I see your point of "better one entry point than 2 starts", but I worry that merging into Epidemic curve article will axe out the "raise the line", logistic, public policy scope. I saw users *remove* content due to such "scope-overflow" rational in the past. This management issues will also get drowned under/below the Epidemic curve's technical sections. Yug (talk) 08:51, 8 April 2020 (UTC)Reply

Can we close this ? It's pretty sure it's a dead end. Yug (talk) 20:17, 13 April 2020 (UTC)Reply

I'd like to have a little more participation first; there are only three of us currently. {{u|Sdkb}}talk 20:34, 13 April 2020 (UTC)Reply
Hello Sdkb, check out Flatten the curve, it's not epidemiology alone anymore and unlikely to fit back into Epidemic curve. Scope are diverging. Yug (talk) 22:45, 13 April 2020 (UTC)Reply
  • Strongly oppose - This one is pandemic-related than a generic dictionary definition. So I agree with Knowledgekid87. Hansen SebastianTalk 23:10, 13 April 2020 (UTC)Reply
  • Oppose on the grounds of these being two different topics and both are likely to expand a lot, given that this overall aspect of science and its relation to civilisation (epidemiology) has dramatically gained importance in the eyes of most of the world's population and decision-making bodies/networks. Epidemic curve could be thought of as a more popular-level simplification of the core of Mathematical modelling of infectious disease, while Flatten the curve is about a choice of social policy and individual decision-making and an explanation of why it makes sense. Epidemic curve could very easily be expanded to explain semilog epidemic curves, which are a key to understanding the exponential growth phase prior to mitigation measures or saturation (herd immunity; you cannot get more than 100% of a population infected), and in a few months' or years' time, looking back at the history of their usage in this pandemic should give info on the sociology/educational aspect - how much did different demographic profiles of ordinary people or political leaders understand the curves and their significance, for example. Flattening the curve will be able to have sourced information added from open-access/open-sourced peer-reviewed research papers that say, for example, if measures X and Y had (or had not) been taken on dates D_1 and D_2 in territory T then the curves would (would not) have "flattened" as shown in the diagram from the paper and N COVID-19 deaths would (would not) have been avoided. Boud (talk) 20:54, 15 April 2020 (UTC)Reply

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You can see the reason for deletion at the file description page linked above. —Community Tech bot (talk) 05:38, 3 June 2020 (UTC)Reply