數據 (The data)

With the number of cases steadily rising day by day, COVID-19 has been pretty much in the headlines of every newspaper known to man. Despite the massive amount of attention, a topic that has remained mostly untouched (some exceptions being the reports of farm and domestic animals getting infected) by the mainstream media is how animals are hit by the disease too. To cite the information provided by the government of Canada1 “There is currently limited information on animals and COVID-19, especially on whether an animal can spread the virus if they become infected. “

隨著案件數量每天穩步上升，COVID-19幾乎已成為每個人所熟知的報紙的頭條新聞。 盡管引起了極大的關注，但主流媒體仍未觸及到這個話題(動物和家畜受到感染的報道除外)，這也是動物如何受到這種疾病襲擊的話題。 引用加拿大政府提供的信息1“目前關于動物和COVID-19的信息有限，尤其是關于動物如果被感染是否可以傳播病毒的信息。 “

There have been admirable efforts by the scientific community to understand how the virus develops, both in animal and human hosts and the research about it grows by the day. Open data regarding animal infections is, however, not so easy to find.

科學界做出了令人欽佩的努力，以了解該病毒在動物和人類宿主中如何發展，并且對它的研究日趨增長。 但是，關于動物感染的公開數據并不是那么容易找到。

To that effect, the World Organisation for Animal Health frequently publishes a report of new cases in animals around the world at this page2. However, compiling information from this source is hard work, and not everyone is willing/has the time to extract the data from each statement and make a dataset out of them. One of the few sources of data open to the public is the one in the United States Department of Agriculture website3. The table lists cases of SAR-CoV-2 (the virus that causes COVID-19 in humans) in animals that have been confirmed by the United States Department of Agriculture’s National Veterinary Services Laboratories. Though in each case, only the first animal of a species reported in a facility or home makes it to the table, and it is, therefore, a rough estimate of how many animals have the virus in the US.

為此，世界動物衛生組織經常在此頁面 2上發布世界各地動物新病例的報告。 但是，從此來源編譯信息是一項艱苦的工作，并不是每個人都愿意/有時間從每個語句中提取數據并從中提取數據集。 公開數據的少數來源之一是美國農業部網站 3中的一種。 該表列出了由美國農業部國家獸醫服務實驗室確認的動物中SAR-CoV-2(在人類中引起COVID-19的病毒)的病例。 盡管在每種情況下，只有設施或家中報告的該物種的第一只動物才會出現在桌子上，因此，它是對美國有多少動物感染該病毒的粗略估計。

Despite its small size (around 30 data points) For each case, the table notes the type of animal infected, where and when it got infected, the method used to detect the virus and whether or not it was in contact with a human infected. The table is not available to download, but it is easy enough to either copy or scrape if you want it. To make things more interesting, I decided to scrap it instead of copying it into an Excel file using the following code:

盡管其體積很小(大約30個數據點)，但表中仍注明了每種動物的感染類型，感染時間和地點，用于檢測病毒的方法以及是否與感染者接觸。 該表不可下載，但如果需要，可以輕松復制或刮取。 為了使事情變得更有趣，我決定使用以下代碼來對其進行剪貼，而不是將其復制到Excel文件中：

import pandas as pd from bs4 import BeautifulSoup import requests#URL URL = 'https://www.aphis.usda.gov/aphis/ourfocus/animalhealth/sa_one_health/sars-cov-2-animals-us'#Final list of results list_of_results = []#Scraping the data animals = requests.get(URL) animals_content = animals.content parser = BeautifulSoup(animals_content, 'html.parser') results1 = parser.find_all('tbody')for x in results1:element = x.find_all('td')for y in element: list_of_results.append(y.text.replace('\n', '').strip())#Separating the data into different lists animals = list_of_results[0::4] date = list_of_results[1::4] state = list_of_results[2::4] method = list_of_results[3::4]#Making a dataframe to work from data = pd.DataFrame() data[animals[0]] = animals[1:] data[date[0]] = date[1:] data[state[0]] = state[1:] data[method[0]] = method[1:]#Original dataset that will remain untouched through the analysis original = data#Adding a column that checks whether or not the animal had contact with def human_checker(row):if '~' in row:return 'Yes'else: return 'No'data['Contact with infected Human'] = data['Type of Animal'].apply(human_checker)

While this is, admittedly a pretty long snip of code for its intended purpose, it does its job and results in a table that you can work with using Python if that’s your choice. Its usability, of course, depends on the table staying just as it is while they add cases (which I doubt will happen as the table should be able to grow in size and complexity with more data coming in). If you’d like to look more closely at the preparation process, you are welcome to visit my Github page and the NBViewer which hosts the whole process.

盡管誠然，這是達到預期目的的一長段代碼，但它確實可以完成工作，并且會生成一個表，您可以選擇使用該表來使用Python。 當然，它的可用性取決于表在添加案例時保持原樣的狀態(我懷疑這種情況會發生，因為表應該能夠隨著更多數據的輸入而增加大小和復雜性)。 如果您想更仔細地了解準備過程，歡迎訪問我的Github頁面和托管整個過程的NBViewer 。

分析 (The Analysis)

Source: Graph created by the author using the data from the United States Department of Agriculture account of COVID-19 cases in animals until the day 17th of August3資料來源：該圖是作者使用美國農業部截至8月17日的動物COVID-19病例數據制作而成的圖。

Most animals in the data until now (over 90%) had exposure to a confirmed or probable infected human. However, according to the information published in the CDC’s official website?:

到目前為止，數據中的大多數動物(超過90％)都暴露于確診或可能感染的人類。 但是，根據CDC官方網站上發布的信息the：

“The virus that causes COVID-19 spreads mainly from person to person through respiratory droplets from coughing, sneezing, and talking. Recent studies show that people who are infected but do not have symptoms likely also play a role in the spread of COVID-19. At this time, there is no evidence that animals play a significant role in spreading the virus that causes COVID-19. Based on the limited information available to date, the risk of animals spreading COVID-19 to people is considered low”.

“導致COVID-19的病毒主要通過咳嗽，打噴嚏和說話的呼吸道飛沫在人與人之間傳播。 最近的研究表明，被感染但沒有癥狀的人也可能在COVID-19的傳播中起作用。 目前，沒有證據表明動物在傳播引起COVID-19的病毒方面起著重要作用。 根據迄今為止可獲得的有限信息，認為動物傳播COVID-19到人的風險較低。

Furthermore, the CDC continues in the same report by adding:

此外，疾控中心在同一份報告中繼續增加以下內容：

“We are still learning about this virus, but it appears that it can spread from people to animals in some situations, especially after close contact with a person sick with COVID-19”.

“我們仍在研究這種病毒，但在某些情況下，它似乎可以從人傳播到動物，尤其是在與患有COVID-19的患者密切接觸后”。

Therefore, it is highly likely that the cases in the data had this origin, though it is not the only possible explanation, and it could have other roots too.

因此，數據中的案例很有可能是起源于此的，盡管這不是唯一可能的解釋，它也可能具有其他根源。

Moving on from the possible origin to the animals that contracted the disease, the species of animals infected are of a relatively small variety, as shown in the graph below:

從可能的起源轉到感染該疾病的動物，被感染的動物種類相對較小，如下圖所示：

Source: Graph created by the author using the data from the United States Department of Agriculture account of COVID-19 cases in animals until the day 17th of August3資料來源：該圖是作者使用美國農業部截至8月17日的動物COVID-19病例數據制作而成的圖。

Bar a couple of exceptions (notably the tigers and the lions which contracted the disease at the Bronx Zoo? and a couple of minks), the overwhelming majority of cases recorded belong to cats and dogs. Likewise, the distribution of cases through the United States is limited to a small number of states, with only twelve states out of the fifty have reported cases so far.

除少數例外(特別是在布朗克斯動物園 ?感染這種疾病的老虎和獅子以及幾只水貂)外，記錄的絕大多數病例都屬于貓和狗。 同樣，通過美國分配的案件僅限于少數幾個州，迄今為止，在五十個州中只有十二個州報告了案件。

Source: Graph created by the author using the data from the United States Department of Agriculture account of COVID-19 cases in animals until the day 17th of August3資料來源：該圖是作者使用美國農業部截至8月17日的動物COVID-19病例數據制作而成的圖。

New York with nine cases and Utah with eight are the states with the most cases reported so far, followed by Texas with three. The other nine states only have one contagion each.

紐約是九例，猶他州是八例，是迄今為止報告最多的州，其次是德克薩斯州，是三例。 其他九個州每個州只有一個傳染病。

Source: Graph created by the author using the data from the United States Department of Agriculture account of COVID-19 cases in animals until the day 17th of August3資料來源：該圖是作者使用美國農業部截至8月17日的動物COVID-19病例數據制作而成的圖。

Until now, July is the month with most infections reported, with the current month as a relatively close second despite it not being finished yet, which makes it likely that the trend upward will keep on its course. Lastly, it is worth noting the methods used for diagnosis of the disease so far, as plotted below:

到目前為止，7月是報告感染最多的月份，盡管還沒有結束，但本月仍是第二個月，這使得上升趨勢可能會繼續下去。 最后，值得注意的是，到目前為止，該疾病的診斷方法如下圖所示：

Source: Graph created by the author using the data from the United States Department of Agriculture account of COVID-19 cases in animals until the day 17th of August3資料來源：該圖是作者使用美國農業部截至8月17日的動物COVID-19病例數據制作而成的圖。

Most of the conditions were recognised using the PCR-test, which, on the authority of the FDA?, serves to test if there is an active coronavirus infection. The other test administered most regularly detects antibodies (Ab) produced by the immune system to stop the sickness.

大多數條件是通過PCR試驗識別的，該試驗是根據FDA the的授權進行的 ，用于檢驗是否存在活動性冠狀病毒感染。 進行的另一項測試最定期地檢測由免疫系統產生的抗體(Ab)，以阻止疾病。

結論 (Conclusion)

While there is little data to say anything decisive just yet, there are a couple of starting trends that are worth looking at:

盡管目前尚無數據可以說出決定性的內容，但是有幾個值得關注的起始趨勢：

• For as long as three months, cases of COVID-19 in animals have been steadily rising, and the number of cases in August so far suggests that it may continue.
  在長達三個月的時間里，動物中的COVID-19病例一直在穩步上升，到目前為止，八月份的病例數表明這種情況可能會持續下去。

• While the full list of species that can contract the virus is still unknown, the scientific community has been working non-stop to understand whether or not farm animals can contract the sickness too. So far, according to this source1, ducks, chicken and pigs have resistance to the virus.

  盡管尚不清楚可感染該病毒的物種的完整列表，但科學界一直在不停地努力了解農場動物是否也可感染該病。 到目前為止， 根據該來源 1，鴨，雞和豬對這種病毒具有抗藥性。

• A good percentage of the animals tested have had the infection in the past and developed antibodies to fight it.
  過去測試過的動物中，有很大一部分曾經感染過這種病毒，并開發出抗擊它的抗體。

Most of this information depends on what the near future might hold, and the listed trends can either be reversed or proved correct.

這些信息大部分取決于不久的將來會怎樣，列出的趨勢可以逆轉或證明是正確的。

[1]: Government of Canada, Coronavirus disease (COVID-19) > Prevention and risks, (2020)

[1]：加拿大政府， 冠狀病毒病(COVID-19)>預防和風險 ，(2020年)

[2]: World Organisation for Animal Health, Event in animals, (2020)

[2]：世界動物衛生組織， 動物事件 ，(2020年)

[3]: United States Department of Agriculture (USDA), Confirmed cases of SARS-CoV-2 in Animals in the United States, (2020)

[3]：美國農業部(USDA)，美國確診為動物的SARS-CoV-2病例 ，(2020年)

[4]: Centers for Disease Control and Prevention (CDC), COVID-19 and Animals, (2020)

[4]：疾病預防控制中心(CDC)， COVID-19和動物 ，(2020年)

[5]: N. Daly, Seven more big cats test positive for coronavirus at Bronx Zoo, National Geographic, (2020)

[5]：戴利(N. Daly) ，《國家地理》 ， 布朗克斯動物園，另外七只大貓的冠狀病毒測試呈陽性 ，(2020年)

[6]: U.S Foods and Drugs Administration (FDA), Coronavirus Testing Basics, (2020)

[6]：美國食品和藥物管理局(FDA)， 冠狀病毒檢測基礎知識 (2020)

翻譯自: https://towardsdatascience.com/exploring-the-data-of-animals-infected-with-covid-19-50ce1ed16edd

總結

以上是生活随笔為你收集整理的探索感染了COVID-19的动物的数据的全部內容，希望文章能夠幫你解決所遇到的問題。

如果覺得生活随笔網站內容還不錯，歡迎將生活随笔推薦給好友。