<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>JackFr</author><text>&amp;gt; Half of the people I know are working from home and stocked up on 1-2 months of food at the outset of this.&lt;p&gt;Seriously?  Your personal network is evidence the this study is useless because of sampling bias?&lt;p&gt;Everyone I know voted for Hilary Clinton and yet here we are.&lt;p&gt;&amp;gt; People who are shopping in stores are absolutely a very biased sample.&lt;p&gt;People who have jobs that allow them to work from home are a very biased sample. How many grocery stockers are there in NYC compared to let’s say, software developers?  I suspect you haven’t a clue, since by your own admission you don’t know a single person who needs to leave their home to work.  So maybe your mental model if who makes up the population is skewed.</text><parent_chain><item><author>koheripbal</author><text>As a (40-something) NYC resident, I don&amp;#x27;t believe that is accurate.  Half of the people I know are working from home and stocked up on 1-2 months of food at the outset of this.  The other half left the city and are now staying with friends&amp;#x2F;family in other states or have rented homes elsewhere.&lt;p&gt;Those that did stay and still need food (ie produce) are having it delivered.&lt;p&gt;People who are shopping in stores are absolutely a very biased sample.&lt;p&gt;Very specifically, this bias excludes older people who are locking themselves away very very judiciously.</text></item><item><author>mannykannot</author><text>NYC is not suburbia. I believe a higher percentage are still working outside of their homes (and, in many cases, that also means travelling on public transport), and a smaller percentage have the financial and transport resources to significantly reduce the frequency of their shopping trips. Apartment living means a greater exposure to your neighbors whenever you do enter or exit. The sampling in NYC, while far from ideal, may therefore be better than the other regions, in that shopping behaviour may not be as dominant a risk factor as you suppose.&lt;p&gt;For the same reasons, plus the likelehood that the virus arrived in NYC early and frequently, NYC&amp;#x27;s figures cannot be extrapolated to the rest of the state or country.&lt;p&gt;I would like to see how these figures match up to the sewage-sampling method of estimation.</text></item><item><author>wtvanhest</author><text>&amp;quot;Preliminary test results suggest 21% of NYC residents have Covid antibodies&amp;quot;&lt;p&gt;Should be re-written as:&lt;p&gt;&amp;quot;Preliminary test results suggest 21% of of people approached in a crowded grocery store and who would agree to give blood have Covid antibodies&amp;quot;&lt;p&gt;All of these tests suffer the same sample bias, and that sample bias is massive.&lt;p&gt;People who are already in a grocery store (risky behavior), who are willing to give a blood sample (believes they may have been previously exposed) are not the same as people who are leaving their house only for very limited purposes and ordering food online.&lt;p&gt;If we assume that the % of people shopping in grocery stores and willing to take the test are in risk group A, and the people not shopping are in risk group B.  We can run the following quick analysis.&lt;p&gt;First, assume risk group A is 5 times as likely to have had COVID than Risk group B (but plug any assumption in there necessary)&lt;p&gt;Then assume that risk group A is only 10% of the population, then rerun the numbers as follows:&lt;p&gt;For every 100 people in risk group A who tested, 21 were positive.&lt;p&gt;Risk group A is 100 people, and risk group B is 900.&lt;p&gt;Risk group A&amp;#x27;s 100 were 21 prior positive.
Risk group B&amp;#x27;s 900 could be estimated that 4.2 people per 100 were positive, so in total of the 900 people 37.8 were positive.&lt;p&gt;21+37.8 = 59 people of 1000, or 5.8%.&lt;p&gt;Plug any numbers you want in the analysis, but the assumptions drive huge variability in the % of New Yorkers infected.  Without a less biased sample, we really don&amp;#x27;t know much other than that way less than 21% of New Yorkers have anti-bodies.</text></item><item><author>TheBlight</author><text>Sure all of these studies are potentially flawed but they&amp;#x27;re all generally pointing in the same direction. There are many more infections than we know about and the CFR is not anywhere close to the actual IFR.&lt;p&gt;NYC is an outlier with a 21% infection estimate but for the rest of NY (outside NYC metro&amp;#x2F;Westchester&amp;#x2F;LI) the estimate is 3.6%. Santa Clara estimate was 3%. LA County estimate was 4%. Seems like a trend is developing.</text></item><item><author>aazaa</author><text>&amp;gt; In his press conference today, Governor Cuomo revealed the preliminary results of a first-phase antibody test that surveyed 3,000 New Yorkers over two days in 19 counties at 40 locations that included grocery and big-box stores. The sample suggests that 13.9% of New York State residents have the antibodies, meaning they had the virus at one point and recovered. Of the regions tested–Long Island, NYC, Westchester&amp;#x2F;Rockland, and the rest of the State–New York City had the highest positive rate at 21.2%. The potential good news to come to light is that the death rate may be far lower than some estimates, at 0.5%.&lt;p&gt;This still is not a random sampling. It only samples from shoppers at grocery stores and big-box retailers. Imagine doing the same study, but of people who ordered groceries online only. Would you expect to see big differences in exposure rate? I think so.&lt;p&gt;The study itself isn&amp;#x27;t linked anywhere, nor have I seen it elsewhere. Science is all about the details. It&amp;#x27;s not hard to imagine half a dozen ways that the bottom line result of this study could have been skewed by decisions made by the study authors and ground team.</text></item></parent_chain></comment><story><title>Preliminary test results suggest 21% of NYC residents have Covid antibodies</title><url>https://www.6sqft.com/new-york-covid-antibody-test-preliminary-results/</url></story>
<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>gwright</author><text>&amp;gt;  Half of the people I know are working from home and stocked up on 1-2 months of food at the outset of this.&lt;p&gt;This surprises me if for no other reason than it takes a lot of space to store 1-2 months of food. Might be true, but is certainly different than what is going on in suburban Connecticut based on my social network.</text><parent_chain><item><author>koheripbal</author><text>As a (40-something) NYC resident, I don&amp;#x27;t believe that is accurate.  Half of the people I know are working from home and stocked up on 1-2 months of food at the outset of this.  The other half left the city and are now staying with friends&amp;#x2F;family in other states or have rented homes elsewhere.&lt;p&gt;Those that did stay and still need food (ie produce) are having it delivered.&lt;p&gt;People who are shopping in stores are absolutely a very biased sample.&lt;p&gt;Very specifically, this bias excludes older people who are locking themselves away very very judiciously.</text></item><item><author>mannykannot</author><text>NYC is not suburbia. I believe a higher percentage are still working outside of their homes (and, in many cases, that also means travelling on public transport), and a smaller percentage have the financial and transport resources to significantly reduce the frequency of their shopping trips. Apartment living means a greater exposure to your neighbors whenever you do enter or exit. The sampling in NYC, while far from ideal, may therefore be better than the other regions, in that shopping behaviour may not be as dominant a risk factor as you suppose.&lt;p&gt;For the same reasons, plus the likelehood that the virus arrived in NYC early and frequently, NYC&amp;#x27;s figures cannot be extrapolated to the rest of the state or country.&lt;p&gt;I would like to see how these figures match up to the sewage-sampling method of estimation.</text></item><item><author>wtvanhest</author><text>&amp;quot;Preliminary test results suggest 21% of NYC residents have Covid antibodies&amp;quot;&lt;p&gt;Should be re-written as:&lt;p&gt;&amp;quot;Preliminary test results suggest 21% of of people approached in a crowded grocery store and who would agree to give blood have Covid antibodies&amp;quot;&lt;p&gt;All of these tests suffer the same sample bias, and that sample bias is massive.&lt;p&gt;People who are already in a grocery store (risky behavior), who are willing to give a blood sample (believes they may have been previously exposed) are not the same as people who are leaving their house only for very limited purposes and ordering food online.&lt;p&gt;If we assume that the % of people shopping in grocery stores and willing to take the test are in risk group A, and the people not shopping are in risk group B.  We can run the following quick analysis.&lt;p&gt;First, assume risk group A is 5 times as likely to have had COVID than Risk group B (but plug any assumption in there necessary)&lt;p&gt;Then assume that risk group A is only 10% of the population, then rerun the numbers as follows:&lt;p&gt;For every 100 people in risk group A who tested, 21 were positive.&lt;p&gt;Risk group A is 100 people, and risk group B is 900.&lt;p&gt;Risk group A&amp;#x27;s 100 were 21 prior positive.
Risk group B&amp;#x27;s 900 could be estimated that 4.2 people per 100 were positive, so in total of the 900 people 37.8 were positive.&lt;p&gt;21+37.8 = 59 people of 1000, or 5.8%.&lt;p&gt;Plug any numbers you want in the analysis, but the assumptions drive huge variability in the % of New Yorkers infected.  Without a less biased sample, we really don&amp;#x27;t know much other than that way less than 21% of New Yorkers have anti-bodies.</text></item><item><author>TheBlight</author><text>Sure all of these studies are potentially flawed but they&amp;#x27;re all generally pointing in the same direction. There are many more infections than we know about and the CFR is not anywhere close to the actual IFR.&lt;p&gt;NYC is an outlier with a 21% infection estimate but for the rest of NY (outside NYC metro&amp;#x2F;Westchester&amp;#x2F;LI) the estimate is 3.6%. Santa Clara estimate was 3%. LA County estimate was 4%. Seems like a trend is developing.</text></item><item><author>aazaa</author><text>&amp;gt; In his press conference today, Governor Cuomo revealed the preliminary results of a first-phase antibody test that surveyed 3,000 New Yorkers over two days in 19 counties at 40 locations that included grocery and big-box stores. The sample suggests that 13.9% of New York State residents have the antibodies, meaning they had the virus at one point and recovered. Of the regions tested–Long Island, NYC, Westchester&amp;#x2F;Rockland, and the rest of the State–New York City had the highest positive rate at 21.2%. The potential good news to come to light is that the death rate may be far lower than some estimates, at 0.5%.&lt;p&gt;This still is not a random sampling. It only samples from shoppers at grocery stores and big-box retailers. Imagine doing the same study, but of people who ordered groceries online only. Would you expect to see big differences in exposure rate? I think so.&lt;p&gt;The study itself isn&amp;#x27;t linked anywhere, nor have I seen it elsewhere. Science is all about the details. It&amp;#x27;s not hard to imagine half a dozen ways that the bottom line result of this study could have been skewed by decisions made by the study authors and ground team.</text></item></parent_chain></comment><story><title>Preliminary test results suggest 21% of NYC residents have Covid antibodies</title><url>https://www.6sqft.com/new-york-covid-antibody-test-preliminary-results/</url></story>