diff --git a/README.md b/README.md index d0e8759b9..c137c881d 100644 --- a/README.md +++ b/README.md @@ -91,6 +91,7 @@ In order to convert the Rmd files to HTML files for Hugo you also need to: - `local=TRUE` similar to `-D` to process draft files - `run_hugo=FALSE` to manually run hugo - `build_rmd=TRUE` force a (re)build of the Rmd pages +1. Run blogdown to convert a single file to HTML: `Rscript -e 'blogdown::build_site(local=TRUE, run_hugo=FALSE, build_rmd="content/blog/.Rmd")'` 1. Alternatively, run `npm run build:blog` 1. Run Hugo server as usual diff --git a/config.toml b/config.toml index 0c184e9b2..a7855a7ba 100644 --- a/config.toml +++ b/config.toml @@ -114,6 +114,6 @@ relativeURLs = false feedbackForm = "https://docs.google.com/forms/d/e/1FAIpQLSeIeOJtrAhdOriEyiRY7LkpQX8DZBY19dl6De8l56Q9CZhmxw/viewform?usp=pp_url&entry.1245962748=" feedbackLikelihoodMobile = 0.2 feedbackLikelihoodDesktop = 1 - feedbackDelayMin = 10 # in sec - feedbackDelayMax = 100 # in sec - feedbackDuration = 60 # show it for 60sec \ No newline at end of file + feedbackDelayMin = 45 # in sec + feedbackDelayMax = 180 # in sec + feedbackDuration = 60 # show it for 60sec \ No newline at end of file diff --git a/content/blog/2021-01-21-unpack-cfr.Rmd b/content/blog/2021-01-21-unpack-cfr.Rmd index fe659e129..57d8b6591 100644 --- a/content/blog/2021-01-21-unpack-cfr.Rmd +++ b/content/blog/2021-01-21-unpack-cfr.Rmd @@ -344,7 +344,7 @@ td {font-size: 13px}
|||Florida|||National|| |:-:|:-:|:-:|:-:|:-:|:-:|:-:| -| **Age group** | **2020-04-01** | **2020-11-01** | **04-01 to 11-01** | **2020-04-01** | **2020-11-01** | **04-01 to 11-01** | +| **Age group** | **2020-04-01** | **2020-12-01** | **04-01 to 12-01** | **2020-04-01** | **2020-12-01** | **04-01 to 12-01** | | aggregate | 0.23 (0.2, 0.27) | 0.16 (0.12, 0.19) | -0.33 (-0.52, -0.094) | 0.34 (0.32, 0.35) | 0.13 (0.11, 0.15) | -0.61 (-0.67, -0.56) | | 20-29 | \- | \- | \- | 0.025 (0.019, 0.03) | 0.0066 (0.0014, 0.012) | -0.73 (-0.95, -0.43) | | 30-39 | \- | \- | \- | 0.049 (0.045, 0.054) | 0.019 (0.014, 0.025) | -0.61 (-0.72, -0.48) | diff --git a/content/blog/2021-01-21-unpack-cfr.html b/content/blog/2021-01-21-unpack-cfr.html index 9dc66b905..5cab7fd20 100644 --- a/content/blog/2021-01-21-unpack-cfr.html +++ b/content/blog/2021-01-21-unpack-cfr.html @@ -471,11 +471,11 @@

Age-Stratified HFR

Age group 2020-04-01 -2020-11-01 -04-01 to 11-01 +2020-12-01 +04-01 to 12-01 2020-04-01 -2020-11-01 -04-01 to 11-01 +2020-12-01 +04-01 to 12-01 aggregate diff --git a/content/blog/2021-01-22-holiday-surveys.Rmd b/content/blog/2021-01-22-holiday-surveys.Rmd new file mode 100644 index 000000000..2ed398a0f --- /dev/null +++ b/content/blog/2021-01-22-holiday-surveys.Rmd @@ -0,0 +1,425 @@ +--- +title: "Home for the Holidays? The Impact of US Holidays on Social Behaviors and Preventative Measures" +author: "Leanna Morinishi, Kris Barkume, Esther Kim, and Alex Reinhart" +date: 2021-02-02 +tags: + - COVIDcast + - symptom surveys + - R +summary: | + How did Thanksgiving and Christmas affect travel, social, and preventative + behaviors in the USA during the COVID-19 pandemic? +heroImage: /blog/images/holiday-gathering.jpg +heroImageThumb: /blog/images/holiday-gathering-small.jpg +authors: + - lmorinishi + - kbarkume + - ekim + - alex +related: + - 2021-01-28-survey-vaccines + - 2020-12-10-masks-public + - 2020-10-06-survey-wave-4 +acknowledgements: | + Facebook's survey team, including Andy Garcia, Travis Leleu, Patrick Xu, Sarah + LaRocca, and Katherine Morris assisted with the analysis for this post. Kelsey + Mulcahy at Facebook Data For Good helped coordinate data access for numerous + researchers. +output: + blogdown::html_page: + toc: true +--- + +With pandemic fatigue setting in across the United States after a long year +filled with uncertainty, many felt the temptation to celebrate a “normal” +Thanksgiving and Christmas. However, with cases steeply rising across the US, +the risk of transmission when gathering with friends and family only increased +throughout the fall. Many health organizations strongly discouraged large +gatherings during the holidays and a number of states expanded COVID-19 +restrictions to prevent further escalation in cases. +[Reports](https://www.washingtonpost.com/travel/2020/12/21/christmas-flights-cdc-restrictions-covid/) +from airlines suggest air travel was up significantly during the holiday season, +but `r blogdown::shortcode_html("reflink", "surveys", "Delphi’s COVID-19 Surveys")` can +provide a broader picture of the travel Americans took during the holiday +season. In taking greater risks with travel, did Americans change their +behaviors in other preventative measures like mask wearing during this time? + +For the following analyses, we use publicly available aggregate data from the +`r blogdown::shortcode_html("apireflink", "api/covidcast.html", "COVIDcast Epidata API")` that have +been `r blogdown::shortcode_html("apireflink", "api/covidcast-signals/fb-survey.html#survey-weighting", "weighted to better match state demographics")`. +Here we focus on behavioral signals which have been available since September 8, +2020, when `r blogdown::shortcode_html("reflink", "2020-10-06-survey-wave-4", "Wave 4 of the survey was deployed")`, +and are now visible in the `r blogdown::shortcode_html("reflink", "survey-results", "Delphi Group’s survey dashboard")`. Additionally, we +only consider data after November 11, 2020 to avoid any major effects due to the +US election on November 3. All data below will be based on 7-day rolling +averages of survey responses. + +## Travel and Other Social Behaviors During US Holidays + +Despite [warnings from the +CDC](https://www.cdc.gov/coronavirus/2019-ncov/daily-life-coping/holidays.html) +that the “safest way to celebrate is at home with people who live with you”, the +[TSA screened approximately 9.5 million airline +passengers](https://www.tsa.gov/news/press/releases/2020/12/01/tsa-holiday-screening-volumes-tick-above-1m-several-days-during) +during the 2020 Thanksgiving holiday travel period (about 35-45% of 2019 volumes +during the same time frame). +[Reports](https://www.washingtonpost.com/travel/2020/12/21/christmas-flights-cdc-restrictions-covid/) +from airlines suggested that travel reached its highest levels since the start +of the pandemic during the Christmas holiday with about 1% of the US population +taking flights in just the few days surrounding the holiday. + +```{r traveled-recently, message=FALSE, fig.width=9, out.extra = 'class="wide-figure"'} +library(covidcast) +library(ggplot2) +library(stringr) +library(dplyr) +library(grid) +library(gridExtra) + +start_after_election <- "2020-11-10" +end_day <- "2021-01-05" + +statelist <- c('AK', 'AZ', 'CA', 'CO', 'ID', 'MT', 'NV', 'NM', 'OR', 'UT', + 'WA', 'WY', 'HI', 'IL', 'IN', 'IA', 'KS', 'MI', 'MN', 'MO', + 'NE', 'ND', 'OH', 'SD', 'WI', 'CT', 'ME', 'MA', 'NH', 'NJ', + 'NY', 'PA', 'RI', 'VT', 'AL', 'AR', 'DE', 'FL', 'GA', 'KY', + 'LA', 'MD', 'MS', 'NC', 'OK', 'SC', 'TN', 'TX', 'WV', 'VA') +regions <- rep(c('West', 'Midwest', 'Northeast', 'South'), + times = c(13, 12, 9, 16)) + +travel <- covidcast_signal("fb-survey", + "smoothed_wtravel_outside_state_5d", + start_day = start_after_election, end_day = end_day, + geo_type = "state") + +travel_normed <- travel %>% + rename(state = geo_value, date = time_value) %>% + select(date, state, value, sample_size) %>% + mutate(state = str_to_upper(state)) %>% + filter(state %in% statelist) %>% + mutate(Region = plyr::mapvalues(state, statelist, regions)) %>% + group_by(state) %>% + mutate(normed = value * 100 / first(value) - 100) %>% + ungroup() %>% + group_by(date, Region) %>% + summarise_at("normed", list(mean = ~mean(.), sd = ~sd(.), se = ~sd(.)/sqrt(n()) )) + +regionmap <- travel %>% + filter(geo_value %in% str_to_lower(statelist)) %>% + mutate(value = plyr::mapvalues(geo_value, str_to_lower(statelist), regions), + value = as.integer(factor(value))) + +grid_label <- textGrob("Data from Delphi COVIDcast, delphi.cmu.edu", + hjust = 1, x = 1, gp = gpar(fontsize = 9)) + +g1 <- travel_normed %>% + ggplot() + + geom_vline(xintercept = as.Date("2020-11-26"), + linetype = "dashed", size = 1.5, color = "darkgrey") + + geom_vline(xintercept = as.Date("2020-12-25"), + linetype = "dashed", size = 1.5, color = "darkgrey") + + geom_line(aes(x = date, y = mean, color = Region)) + + geom_ribbon(aes(x = date, ymin = mean - se, ymax = mean + se, fill = Region), + alpha = 0.2) + + scale_x_date(date_breaks = "2 weeks", + date_labels = "%b %d %Y", + date_minor_breaks = "1 week") + + labs(x = "Date", y = "% traveled out-of-state in last 5 days", + title = "Relative out-of-state travel by US region", + subtitle = "From Delphi's surveys, conducted through Facebook") + + theme_bw() + + theme(legend.position = c(0.095, 0.8)) + + guides(color = FALSE) + +g2 <- plot(regionmap, + title = "US Regions", + choro_col = c("#F8766D", "#7CAE00", "#00BFC4", "#C77CFF"), + choro_params = list(breaks = c(1, 2, 3, 4))) + + theme(legend.position = "none") + +lay <- rbind(c(1,1,1,2), + c(1,1,1,2)) +grid.arrange(g1, g2, nrow = 1, bottom = grid_label, layout_matrix=lay) +``` + +In the COVID-19 survey, we see an increase in self-reported out-of-state travel +in this time frame by surveyed adults. The figure above depicts the normalized +percent of survey respondents who recently traveled out-of-state for 4 US +regions (mean ± s.e. of states in region). Because different states have +different baseline travel behaviors, values in the above figure are relative to +out-of-state travel reported on November 11, 2020. While there was some +variation between states, it appears that out-of-state travel around +Thanksgiving and Christmas day (vertical gray dashed lines) rose steeply in all +regions in the US. We note that since we are using a 7-day average, a travel +peak on or very close to Thanksgiving day would show up 3 to 4 days later in our +data, which is what we observe. + +While the increase in out-of-state travel appears dramatic during Thanksgiving, +the observed increase is less than the typical increase in travel around the +holiday. The [Bureau of Transportation +Statistics](https://www.bts.gov/archive/publications/america_on_the_go/us_holiday_travel/entire) +notes that long distance trips (as defined by travel greater than 50 miles away) +usually increase by 54% in the 6 days surrounding Thanksgiving. In contrast, the +percentage increase in travel found in the survey was closer to 20%. For the +Christmas through New Years time period, the increase in individuals reporting +out-of-state travel in the survey is ~30%, which more closely matches prior year +estimates from the Bureau of Transportation Statistics of 23%. Overall though, +the out-of-state travel reported in the CSS is still down compared to earlier +months in the pandemic. + +```{r spent-time, message=FALSE} +spent_time <- covidcast_signal("fb-survey", + "smoothed_wspent_time_1d", + start_day = start_after_election, end_day = end_day, + geo_type = "state") + +spent_time_stats <- spent_time %>% + rename(state = geo_value, date = time_value) %>% + select(date, state, value, sample_size) %>% + mutate(state = str_to_upper(state)) %>% + filter(state %in% statelist) %>% + mutate(Region = plyr::mapvalues(state, statelist, regions)) %>% + group_by(date, Region) %>% + summarise_at("value", list(mean = ~mean(.), sd = ~sd(.), se = ~sd(.)/sqrt(n()) )) + +spent_time_stats %>% + ggplot() + + geom_vline(xintercept = as.Date("2020-11-26"), + linetype = "dashed", size = 1.5, color = "darkgrey") + + geom_vline(xintercept = as.Date("2020-12-25"), + linetype = "dashed", size = 1.5, color = "darkgrey") + + geom_line(aes(x = date, y = mean, color = Region)) + + geom_line(aes(x = date, y = mean, color = Region)) + + geom_ribbon(aes(x = date, ymin = mean - se, ymax = mean + se, fill = Region), + alpha = 0.2) + + scale_x_date(date_breaks = "2 weeks", + date_labels = "%b %d %Y", + date_minor_breaks = "1 week") + + labs(x = "Date", y = "% spent time with non-household member in past 24h", + title = "Percent surveyed that spent time with a non-household member", + subtitle = "7-day rolling average", + caption = "Data from Delphi COVIDcast, delphi.cmu.edu") + + theme_bw() + + theme(legend.position = c(0.095, 0.2)) + + guides(color = FALSE) + +``` + +Through the survey, we also find that more people in many states spent time with +people outside of their household in social gatherings for Thanksgiving and +Christmas when compared to the preceding week. In the above figure, the percent +of surveyed adults who recently spent time with non-household members clearly +rises around the holidays for all 4 US regions (mean ± s.e. of states in +region). + +Experts had suggested quarantining before the holiday to lower the risk of +spreading COVID-19 during family gatherings. We see a steady decrease in the +number of people reporting contact outside of the household in the 14 days +before Thanksgiving across all regions, possibly due to rising case counts +across the nation. However this strong trend is not observed for the Christmas +holiday. The Northeast and South show only very modest decreases in outside +contact in the days just before Christmas, and rates of contact outside the +household in the Midwest and West actually rose steadily during this time. +Overall, we don’t see strong evidence in the data of people proactively +quarantining between the Thanksgiving and Christmas holidays to reduce the +potential for community spread of COVID-19. + +```{r went-shopping, message=FALSE} +shopped <- covidcast_signal("fb-survey", + "smoothed_wshop_1d", + start_day = start_after_election, end_day = end_day, + geo_type = "state") + +shopped_stats <- shopped %>% + rename(state = geo_value, date = time_value) %>% + select(date, state, value, sample_size) %>% + mutate(state = str_to_upper(state)) %>% + filter(state %in% statelist) %>% + mutate(Region = plyr::mapvalues(state, statelist, regions)) %>% + group_by(date, Region) %>% + summarise_at("value", list(mean = ~mean(.), sd = ~sd(.), se = ~sd(.)/sqrt(n()) )) + +shopped_stats %>% + ggplot() + + geom_vline(xintercept = as.Date("2020-11-26"), + linetype = "dashed", size = 1.5, color = "darkgrey") + + geom_vline(xintercept = as.Date("2020-12-25"), + linetype = "dashed", size = 1.5, color = "darkgrey") + + geom_line(aes(x = date, y = mean, color = Region)) + + geom_line(aes(x = date, y = mean, color = Region)) + + geom_ribbon(aes(x = date, ymin = mean - se, ymax = mean + se, fill = Region), + alpha = 0.2) + + scale_x_date(date_breaks = "2 weeks", + date_labels = "%b %d %Y", + date_minor_breaks = "1 week") + + labs(x = "Date", y = "% Went shopping in past 24h", + title = "Percent surveyed that went shopping recently", + subtitle = "7-day rolling average", + caption = "Data from Delphi COVIDcast, delphi.cmu.edu") + + theme_bw() + + theme(legend.position = c(.095, 0.2)) + + guides(color = FALSE) +``` + +Additionally, Thanksgiving and Christmas are major shopping holidays. When asked +if they had gone to the “market, grocery store, or pharmacy” in the past 24 +hours, a high percentage of survey respondents responded they had on +Thanksgiving, Christmas Eve, and Christmas Day (mean ± s.e. of states in +region). Notably, there were steep falls in shopping in the following weeks, +perhaps as people instead chose to spend time indoors with their families. +Typically the days after Thanksgiving and Christmas are among the 10 busiest +in-store retail days of the year, though this trend does not necessarily extend +to grocery stores, pharmacies and the like. As such, the lack of evidence for +the typical post-holiday shopping binges likely reflects the specificity of the +survey question. + +## Preventative Measures and Testing During the US Holidays + +```{r wore-mask, message=FALSE} +masked <- covidcast_signal("fb-survey", + "smoothed_wwearing_mask", + start_day = start_after_election, end_day = end_day, + geo_type = "state") + +masked_stats <- masked %>% + rename(state = geo_value, date = time_value) %>% + select(date, state, value, sample_size) %>% + mutate(state = str_to_upper(state)) %>% + filter(state %in% statelist) %>% + mutate(Region = plyr::mapvalues(state, statelist, regions)) %>% + group_by(date, Region) %>% + summarise_at("value", list(mean = ~mean(.), sd = ~sd(.), se = ~sd(.)/sqrt(n()) )) + +masked_stats %>% + ggplot() + + geom_vline(xintercept = as.Date("2020-11-26"), + linetype = "dashed", size = 1.5, color = "darkgrey") + + geom_vline(xintercept = as.Date("2020-12-25"), + linetype = "dashed", size = 1.5, color = "darkgrey") + + geom_line(aes(x = date, y = mean, color = Region)) + + geom_line(aes(x = date, y = mean, color = Region)) + + geom_ribbon(aes(x = date, ymin = mean - se, ymax = mean + se, fill = Region), + alpha = 0.2) + + scale_x_date(date_breaks = "2 weeks", + date_labels = "%b %d %Y", + date_minor_breaks = "1 week") + + labs(x = "Date", y = "% wore a mask in public in past 5 days", + title = "Percent surveyed who reported wearing a mask in public", + subtitle = "7-day rolling average", + caption = "Data from Delphi COVIDcast, delphi.cmu.edu") + + theme_bw() + + theme(legend.position = c(0.9, 0.2)) + + guides(color = FALSE) + +``` + +While people in the US may have traveled more, shopped more, and spent more time +with non-household members during the holidays, they also reported participating +in preventative measures in public to a greater degree. For example, the percent +of people who say they wore masks most or all of the time while in public in the +past 5 days increased across the nation prior to Thanksgiving and held steady +through the end of the year (mean ± s.e. of states in region). + +Note, however, that this can't be directly interpreted to mean that a certain +percentage of people wear masks in public places---the survey question asks +respondents if they wear masks *most* or all of the time in public, and since +mask usage is self-reported, it might be biased. A recent [Preventing Epidemics +comparison](https://preventepidemics.org/covid19/science/weekly-science-review/january-9-15-2020/) +found that this self-reported data tends to give higher rates of mask use when +compared to direct observations of people in public places, such as through +surveillance cameras at stores, but also found that these direct observations +agree that mask use is increasing. + +```{r tested-recently, message=FALSE} +tested <- covidcast_signal("fb-survey", + "smoothed_wtested_14d", + start_day = start_after_election, end_day = end_day, + geo_type = "state") + +tested_normed <- tested %>% + rename(state = geo_value, date = time_value) %>% + select(date, state, value, sample_size) %>% + mutate(state = str_to_upper(state)) %>% + filter(state %in% statelist) %>% + mutate(Region = plyr::mapvalues(state, statelist, regions)) %>% + group_by(state) %>% + mutate(normed = value*100/first(value) - 100) %>% ungroup() %>% + group_by(date, Region) %>% + summarise_at("normed", list(mean = ~mean(.), sd = ~sd(.), se = ~sd(.)/sqrt(n()) )) + +tested_normed %>% + ggplot() + + geom_vline(xintercept = as.Date("2020-11-26"), + linetype = "dashed", size = 1.5, color = "darkgrey") + + geom_vline(xintercept = as.Date("2020-12-25"), + linetype = "dashed", size = 1.5, color = "darkgrey") + + geom_line(aes(x = date, y = mean, color = Region)) + + geom_line(aes(x = date, y = mean, color = Region)) + + geom_ribbon(aes(x = date, ymin = mean - se, ymax = mean + se, fill = Region), + alpha = 0.2) + + scale_x_date(date_breaks = "2 weeks", + date_labels = "%b %d %Y", + date_minor_breaks = "1 week") + + labs(x = "Date", y = "% tested in past 14 days", + title = "Percent surveyed that were tested recently", + subtitle = "7-day rolling average", + caption = "Data from Delphi COVIDcast, delphi.cmu.edu") + + theme_bw() + + theme(legend.position = c(0.095, 0.2)) + + guides(color = FALSE) + +``` + +Several news agencies reported that the demand for COVID-19 tests [surged before +Thanksgiving](https://www.wsj.com/articles/how-do-i-get-a-covid-19-test-before-thanksgiving-11605918004). +While this was in large part due to rising COVID-19 cases nationwide, it is also +possible that many people chose to test before seeing friends or family during +the holidays. The CDC had urged Americans not to travel for the holidays, but +stated that [for those “who decide to travel, testing can help you do so more +safely.”](https://www.cdc.gov/coronavirus/2019-ncov/daily-life-coping/holidays.html) +In addition, several government agencies [expanded +testing](https://governor.nc.gov/news/north-carolina-provides-covid-19-tests-colleges-universities-across-state-support-testing) +prior to the holiday season to support testing for people who elected to travel +and gather. + +In the above figure, we do see an increase in survey respondents who had +recently been tested for COVID-19 prior to Thanksgiving, and a slight increase +before Christmas (mean ± s.e. of states in region). However, these effects are +fairly weak, and dominated by longer-term trends that likely reflect case count +trends in the region. For example, from mid-November through the end of the year +we see a ~20% fall in self-reported testing in the Midwest, probably an effect +of the [~50% decrease in COVID-19 cases in the +region](https://covidtracking.com/data/charts/regional-cases-per-million) in the +same time period. We therefore see only weak evidence of prophylactic COVID-19 +testing before the holidays. + +Altogether, it is clear that many Americans opted to travel out-of-state and +gather with friends and family for the Thanksgiving and Christmas holidays. +Public health experts provided a variety of recommendations to reduce the risks +associated with holiday celebrations. Unfortunately, the survey data does not +indicate widespread adherence to these guidelines, as we see only weak evidence +of preemptive quarantining or testing for safer holiday gatherings. Overall, our +analysis suggests conflicting pandemic behaviors during the 2020 holidays, where +a vast majority of Americans used preventative measures like mask-wearing in +public, but simultaneously increased the risk for disease spread by gathering +with friends and family, shopping more, and traveling out-of-state. + +## See the Data Yourself! + +Since April 2020, Carnegie Mellon University’s Delphi Group and Facebook’s Data +for Good have partnered to conduct large-scale daily surveys to monitor the +spread and impact of the COVID-19 pandemic in the United States. To date, the +survey has collected more than 50 million responses. In this post, we show how +the data from the `r blogdown::shortcode_html("reflink", "surveys", "COVID-19 survey")` +can be used to provide a broader picture of how American’s risk behaviors and +sentiments amidst a global pandemic. + +All of the above plots were built using aggregate data for the United States +that CMU/Delphi Group & Facebook provide to the public through the `r blogdown::shortcode_html("apireflink", "symptom-survey/", "COVIDcast Epidata API")`, and +visualize in the `r blogdown::shortcode_html("reflink", "/covidcast", "Delphi Group’s survey dashboard")`. Public, aggregate data for the +global COVID-19 survey can be accessed via [University of Maryland's +API](https://covidmap.umd.edu/api.html). We encourage researchers, public health +officials, and the public to use the survey data and tools for their own +analyses. Microdata is also [available upon +request](https://dataforgood.fb.com/docs/covid-19-symptom-survey-request-for-data-access/) +to academic and nonprofit researchers under data license agreements. diff --git a/content/blog/2021-01-22-holiday-surveys.html b/content/blog/2021-01-22-holiday-surveys.html new file mode 100644 index 000000000..e42c72c1e --- /dev/null +++ b/content/blog/2021-01-22-holiday-surveys.html @@ -0,0 +1,411 @@ +--- +title: "Home for the Holidays? The Impact of US Holidays on Social Behaviors and Preventative Measures" +author: "Leanna Morinishi, Kris Barkume, Esther Kim, and Alex Reinhart" +date: 2021-02-02 +tags: + - COVIDcast + - symptom surveys + - R +summary: | + How did Thanksgiving and Christmas affect travel, social, and preventative + behaviors in the USA during the COVID-19 pandemic? +heroImage: /blog/images/holiday-gathering.jpg +heroImageThumb: /blog/images/holiday-gathering-small.jpg +authors: + - lmorinishi + - kbarkume + - ekim + - alex +related: + - 2021-01-28-survey-vaccines + - 2020-12-10-masks-public + - 2020-10-06-survey-wave-4 +acknowledgements: | + Facebook's survey team, including Andy Garcia, Travis Leleu, Patrick Xu, Sarah + LaRocca, and Katherine Morris assisted with the analysis for this post. Kelsey + Mulcahy at Facebook Data For Good helped coordinate data access for numerous + researchers. +output: + blogdown::html_page: + toc: true +--- + + + + + +

With pandemic fatigue setting in across the United States after a long year +filled with uncertainty, many felt the temptation to celebrate a “normal” +Thanksgiving and Christmas. However, with cases steeply rising across the US, +the risk of transmission when gathering with friends and family only increased +throughout the fall. Many health organizations strongly discouraged large +gatherings during the holidays and a number of states expanded COVID-19 +restrictions to prevent further escalation in cases. +Reports +from airlines suggest air travel was up significantly during the holiday season, +but {{< reflink "surveys" "Delphi’s COVID-19 Surveys" >}} can +provide a broader picture of the travel Americans took during the holiday +season. In taking greater risks with travel, did Americans change their +behaviors in other preventative measures like mask wearing during this time?

+

For the following analyses, we use publicly available aggregate data from the +{{< apireflink "api/covidcast.html" "COVIDcast Epidata API" >}} that have +been {{< apireflink "api/covidcast-signals/fb-survey.html#survey-weighting" "weighted to better match state demographics" >}}. +Here we focus on behavioral signals which have been available since September 8, +2020, when {{< reflink "2020-10-06-survey-wave-4" "Wave 4 of the survey was deployed" >}}, +and are now visible in the {{< reflink "survey-results" "Delphi Group’s survey dashboard" >}}. Additionally, we +only consider data after November 11, 2020 to avoid any major effects due to the +US election on November 3. All data below will be based on 7-day rolling +averages of survey responses.

+
+

Travel and Other Social Behaviors During US Holidays

+

Despite warnings from the +CDC +that the “safest way to celebrate is at home with people who live with you”, the +TSA screened approximately 9.5 million airline +passengers +during the 2020 Thanksgiving holiday travel period (about 35-45% of 2019 volumes +during the same time frame). +Reports +from airlines suggested that travel reached its highest levels since the start +of the pandemic during the Christmas holiday with about 1% of the US population +taking flights in just the few days surrounding the holiday.

+
library(covidcast)
+library(ggplot2)
+library(stringr)
+library(dplyr)
+library(grid)
+library(gridExtra)
+
+start_after_election <- "2020-11-10"
+end_day <- "2021-01-05"
+
+statelist <- c('AK', 'AZ', 'CA', 'CO', 'ID', 'MT', 'NV', 'NM', 'OR', 'UT',
+               'WA', 'WY', 'HI', 'IL', 'IN', 'IA', 'KS', 'MI', 'MN', 'MO',
+               'NE', 'ND', 'OH', 'SD', 'WI', 'CT', 'ME', 'MA', 'NH', 'NJ',
+               'NY', 'PA', 'RI', 'VT', 'AL', 'AR', 'DE', 'FL', 'GA', 'KY',
+               'LA', 'MD', 'MS', 'NC', 'OK', 'SC', 'TN', 'TX', 'WV', 'VA')
+regions <- rep(c('West', 'Midwest', 'Northeast', 'South'),
+               times = c(13, 12, 9, 16))
+
+travel <- covidcast_signal("fb-survey",
+                           "smoothed_wtravel_outside_state_5d",
+                           start_day = start_after_election, end_day = end_day,
+                           geo_type = "state")
+
+travel_normed <- travel %>%
+  rename(state = geo_value, date = time_value) %>%
+  select(date, state, value, sample_size) %>%
+  mutate(state = str_to_upper(state)) %>%
+  filter(state %in% statelist) %>%
+  mutate(Region = plyr::mapvalues(state, statelist, regions)) %>%
+  group_by(state) %>%
+  mutate(normed = value * 100 / first(value) - 100) %>%
+  ungroup() %>%
+  group_by(date, Region) %>%
+  summarise_at("normed", list(mean = ~mean(.), sd = ~sd(.), se = ~sd(.)/sqrt(n()) ))
+
+regionmap <- travel %>%
+  filter(geo_value %in% str_to_lower(statelist)) %>%
+  mutate(value = plyr::mapvalues(geo_value, str_to_lower(statelist), regions),
+         value = as.integer(factor(value)))
+
+grid_label <- textGrob("Data from Delphi COVIDcast, delphi.cmu.edu",
+                       hjust = 1, x = 1, gp = gpar(fontsize = 9))
+
+g1 <- travel_normed %>%
+  ggplot() +
+  geom_vline(xintercept = as.Date("2020-11-26"),
+             linetype = "dashed", size = 1.5, color = "darkgrey") +
+  geom_vline(xintercept = as.Date("2020-12-25"),
+             linetype = "dashed", size = 1.5, color = "darkgrey") +
+  geom_line(aes(x = date, y = mean, color = Region)) +
+  geom_ribbon(aes(x = date, ymin = mean - se, ymax = mean + se, fill = Region),
+              alpha = 0.2) +
+  scale_x_date(date_breaks = "2 weeks",
+               date_labels = "%b %d %Y",
+               date_minor_breaks = "1 week") +
+  labs(x = "Date", y = "% traveled out-of-state in last 5 days",
+       title = "Relative out-of-state travel by US region",
+       subtitle = "From Delphi's surveys, conducted through Facebook") +
+  theme_bw() +
+  theme(legend.position = c(0.095, 0.8)) +
+  guides(color = FALSE)
+
+g2 <- plot(regionmap,
+           title = "US Regions",
+           choro_col = c("#F8766D", "#7CAE00", "#00BFC4", "#C77CFF"),
+           choro_params = list(breaks = c(1, 2, 3, 4))) +
+    theme(legend.position = "none")
+
+lay <- rbind(c(1,1,1,2),
+             c(1,1,1,2))
+grid.arrange(g1, g2, nrow = 1, bottom = grid_label, layout_matrix=lay)
+

+

In the COVID-19 survey, we see an increase in self-reported out-of-state travel +in this time frame by surveyed adults. The figure above depicts the normalized +percent of survey respondents who recently traveled out-of-state for 4 US +regions (mean ± s.e. of states in region). Because different states have +different baseline travel behaviors, values in the above figure are relative to +out-of-state travel reported on November 11, 2020. While there was some +variation between states, it appears that out-of-state travel around +Thanksgiving and Christmas day (vertical gray dashed lines) rose steeply in all +regions in the US. We note that since we are using a 7-day average, a travel +peak on or very close to Thanksgiving day would show up 3 to 4 days later in our +data, which is what we observe.

+

While the increase in out-of-state travel appears dramatic during Thanksgiving, +the observed increase is less than the typical increase in travel around the +holiday. The Bureau of Transportation +Statistics +notes that long distance trips (as defined by travel greater than 50 miles away) +usually increase by 54% in the 6 days surrounding Thanksgiving. In contrast, the +percentage increase in travel found in the survey was closer to 20%. For the +Christmas through New Years time period, the increase in individuals reporting +out-of-state travel in the survey is ~30%, which more closely matches prior year +estimates from the Bureau of Transportation Statistics of 23%. Overall though, +the out-of-state travel reported in the CSS is still down compared to earlier +months in the pandemic.

+
spent_time <- covidcast_signal("fb-survey",
+                               "smoothed_wspent_time_1d",
+                               start_day = start_after_election, end_day = end_day,
+                               geo_type = "state")
+
+spent_time_stats <- spent_time %>%
+  rename(state = geo_value, date = time_value) %>%
+  select(date, state, value, sample_size) %>%
+  mutate(state = str_to_upper(state)) %>%
+  filter(state %in% statelist) %>%
+  mutate(Region = plyr::mapvalues(state, statelist, regions)) %>%
+  group_by(date, Region) %>%
+  summarise_at("value", list(mean = ~mean(.), sd = ~sd(.), se = ~sd(.)/sqrt(n()) ))
+
+spent_time_stats %>%
+  ggplot() +
+  geom_vline(xintercept = as.Date("2020-11-26"),
+             linetype = "dashed", size = 1.5, color = "darkgrey") +
+  geom_vline(xintercept = as.Date("2020-12-25"),
+             linetype = "dashed", size = 1.5, color = "darkgrey") +
+  geom_line(aes(x = date, y = mean, color = Region)) +
+  geom_line(aes(x = date, y = mean, color = Region)) +
+  geom_ribbon(aes(x = date, ymin = mean - se, ymax = mean + se, fill = Region),
+              alpha = 0.2) +
+  scale_x_date(date_breaks = "2 weeks",
+               date_labels = "%b %d %Y",
+               date_minor_breaks = "1 week") +
+  labs(x = "Date", y = "% spent time with non-household member in past 24h",
+       title = "Percent surveyed that spent time with a non-household member",
+       subtitle = "7-day rolling average",
+       caption = "Data from Delphi COVIDcast, delphi.cmu.edu") +
+  theme_bw() +
+  theme(legend.position = c(0.095, 0.2)) +
+  guides(color = FALSE)
+

+

Through the survey, we also find that more people in many states spent time with +people outside of their household in social gatherings for Thanksgiving and +Christmas when compared to the preceding week. In the above figure, the percent +of surveyed adults who recently spent time with non-household members clearly +rises around the holidays for all 4 US regions (mean ± s.e. of states in +region).

+

Experts had suggested quarantining before the holiday to lower the risk of +spreading COVID-19 during family gatherings. We see a steady decrease in the +number of people reporting contact outside of the household in the 14 days +before Thanksgiving across all regions, possibly due to rising case counts +across the nation. However this strong trend is not observed for the Christmas +holiday. The Northeast and South show only very modest decreases in outside +contact in the days just before Christmas, and rates of contact outside the +household in the Midwest and West actually rose steadily during this time. +Overall, we don’t see strong evidence in the data of people proactively +quarantining between the Thanksgiving and Christmas holidays to reduce the +potential for community spread of COVID-19.

+
shopped <- covidcast_signal("fb-survey",
+                            "smoothed_wshop_1d",
+                            start_day = start_after_election, end_day = end_day,
+                            geo_type = "state")
+
+shopped_stats <- shopped %>%
+  rename(state = geo_value, date = time_value) %>%
+  select(date, state, value, sample_size) %>%
+  mutate(state = str_to_upper(state)) %>%
+  filter(state %in% statelist) %>%
+  mutate(Region = plyr::mapvalues(state, statelist, regions)) %>%
+  group_by(date, Region) %>%
+  summarise_at("value", list(mean = ~mean(.), sd = ~sd(.), se = ~sd(.)/sqrt(n()) ))
+
+shopped_stats %>%
+  ggplot() +
+  geom_vline(xintercept = as.Date("2020-11-26"),
+             linetype = "dashed", size = 1.5, color = "darkgrey") +
+  geom_vline(xintercept = as.Date("2020-12-25"),
+             linetype = "dashed", size = 1.5, color = "darkgrey") +
+  geom_line(aes(x = date, y = mean, color = Region)) +
+  geom_line(aes(x = date, y = mean, color = Region)) +
+  geom_ribbon(aes(x = date, ymin = mean - se, ymax = mean + se, fill = Region),
+              alpha = 0.2) +
+  scale_x_date(date_breaks = "2 weeks",
+               date_labels = "%b %d %Y",
+               date_minor_breaks = "1 week") +
+  labs(x = "Date", y = "% Went shopping in past 24h",
+       title = "Percent surveyed that went shopping recently",
+       subtitle = "7-day rolling average",
+       caption = "Data from Delphi COVIDcast, delphi.cmu.edu") +
+  theme_bw() +
+  theme(legend.position = c(.095, 0.2)) +
+  guides(color = FALSE)
+

+

Additionally, Thanksgiving and Christmas are major shopping holidays. When asked +if they had gone to the “market, grocery store, or pharmacy” in the past 24 +hours, a high percentage of survey respondents responded they had on +Thanksgiving, Christmas Eve, and Christmas Day (mean ± s.e. of states in +region). Notably, there were steep falls in shopping in the following weeks, +perhaps as people instead chose to spend time indoors with their families. +Typically the days after Thanksgiving and Christmas are among the 10 busiest +in-store retail days of the year, though this trend does not necessarily extend +to grocery stores, pharmacies and the like. As such, the lack of evidence for +the typical post-holiday shopping binges likely reflects the specificity of the +survey question.

+
+
+

Preventative Measures and Testing During the US Holidays

+
masked <- covidcast_signal("fb-survey",
+                           "smoothed_wwearing_mask",
+                           start_day = start_after_election, end_day = end_day,
+                           geo_type = "state")
+
+masked_stats <- masked %>%
+  rename(state = geo_value, date = time_value) %>%
+  select(date, state, value, sample_size) %>%
+  mutate(state = str_to_upper(state)) %>%
+  filter(state %in% statelist) %>%
+  mutate(Region = plyr::mapvalues(state, statelist, regions)) %>%
+  group_by(date, Region) %>%
+  summarise_at("value", list(mean = ~mean(.), sd = ~sd(.), se = ~sd(.)/sqrt(n()) ))
+
+masked_stats %>%
+  ggplot() +
+  geom_vline(xintercept = as.Date("2020-11-26"),
+             linetype = "dashed", size = 1.5, color = "darkgrey") +
+  geom_vline(xintercept = as.Date("2020-12-25"),
+             linetype = "dashed", size = 1.5, color = "darkgrey") +
+  geom_line(aes(x = date, y = mean, color = Region)) +
+  geom_line(aes(x = date, y = mean, color = Region)) +
+  geom_ribbon(aes(x = date, ymin = mean - se, ymax = mean + se, fill = Region),
+              alpha = 0.2) +
+  scale_x_date(date_breaks = "2 weeks",
+               date_labels = "%b %d %Y",
+               date_minor_breaks = "1 week") +
+  labs(x = "Date", y = "% wore a mask in public in past 5 days",
+       title = "Percent surveyed who reported wearing a mask in public",
+       subtitle = "7-day rolling average",
+       caption = "Data from Delphi COVIDcast, delphi.cmu.edu") +
+  theme_bw() +
+  theme(legend.position = c(0.9, 0.2)) +
+  guides(color = FALSE)
+

+

While people in the US may have traveled more, shopped more, and spent more time +with non-household members during the holidays, they also reported participating +in preventative measures in public to a greater degree. For example, the percent +of people who say they wore masks most or all of the time while in public in the +past 5 days increased across the nation prior to Thanksgiving and held steady +through the end of the year (mean ± s.e. of states in region).

+

Note, however, that this can’t be directly interpreted to mean that a certain +percentage of people wear masks in public places—the survey question asks +respondents if they wear masks most or all of the time in public, and since +mask usage is self-reported, it might be biased. A recent Preventing Epidemics +comparison +found that this self-reported data tends to give higher rates of mask use when +compared to direct observations of people in public places, such as through +surveillance cameras at stores, but also found that these direct observations +agree that mask use is increasing.

+
tested <- covidcast_signal("fb-survey",
+                           "smoothed_wtested_14d",
+                           start_day = start_after_election, end_day = end_day,
+                           geo_type = "state")
+
+tested_normed <- tested %>%
+  rename(state = geo_value, date = time_value) %>%
+  select(date, state, value, sample_size) %>%
+  mutate(state = str_to_upper(state)) %>%
+  filter(state %in% statelist) %>%
+  mutate(Region = plyr::mapvalues(state, statelist, regions)) %>%
+  group_by(state) %>%
+  mutate(normed = value*100/first(value) - 100) %>% ungroup() %>%
+  group_by(date, Region) %>%
+  summarise_at("normed", list(mean = ~mean(.), sd = ~sd(.), se = ~sd(.)/sqrt(n()) ))
+
+tested_normed %>%
+  ggplot() +
+  geom_vline(xintercept = as.Date("2020-11-26"),
+             linetype = "dashed", size = 1.5, color = "darkgrey") +
+  geom_vline(xintercept = as.Date("2020-12-25"),
+             linetype = "dashed", size = 1.5, color = "darkgrey") +
+  geom_line(aes(x = date, y = mean, color = Region)) +
+  geom_line(aes(x = date, y = mean, color = Region)) +
+  geom_ribbon(aes(x = date, ymin = mean - se, ymax = mean + se, fill = Region),
+              alpha = 0.2) +
+  scale_x_date(date_breaks = "2 weeks",
+               date_labels = "%b %d %Y",
+               date_minor_breaks = "1 week") +
+  labs(x = "Date", y = "% tested in past 14 days",
+       title = "Percent surveyed that were tested recently",
+       subtitle = "7-day rolling average",
+       caption = "Data from Delphi COVIDcast, delphi.cmu.edu") +
+  theme_bw() +
+  theme(legend.position = c(0.095, 0.2)) +
+  guides(color = FALSE)
+

+

Several news agencies reported that the demand for COVID-19 tests surged before +Thanksgiving. +While this was in large part due to rising COVID-19 cases nationwide, it is also +possible that many people chose to test before seeing friends or family during +the holidays. The CDC had urged Americans not to travel for the holidays, but +stated that for those “who decide to travel, testing can help you do so more +safely.” +In addition, several government agencies expanded +testing +prior to the holiday season to support testing for people who elected to travel +and gather.

+

In the above figure, we do see an increase in survey respondents who had +recently been tested for COVID-19 prior to Thanksgiving, and a slight increase +before Christmas (mean ± s.e. of states in region). However, these effects are +fairly weak, and dominated by longer-term trends that likely reflect case count +trends in the region. For example, from mid-November through the end of the year +we see a ~20% fall in self-reported testing in the Midwest, probably an effect +of the ~50% decrease in COVID-19 cases in the +region in the +same time period. We therefore see only weak evidence of prophylactic COVID-19 +testing before the holidays.

+

Altogether, it is clear that many Americans opted to travel out-of-state and +gather with friends and family for the Thanksgiving and Christmas holidays. +Public health experts provided a variety of recommendations to reduce the risks +associated with holiday celebrations. Unfortunately, the survey data does not +indicate widespread adherence to these guidelines, as we see only weak evidence +of preemptive quarantining or testing for safer holiday gatherings. Overall, our +analysis suggests conflicting pandemic behaviors during the 2020 holidays, where +a vast majority of Americans used preventative measures like mask-wearing in +public, but simultaneously increased the risk for disease spread by gathering +with friends and family, shopping more, and traveling out-of-state.

+
+
+

See the Data Yourself!

+

Since April 2020, Carnegie Mellon University’s Delphi Group and Facebook’s Data +for Good have partnered to conduct large-scale daily surveys to monitor the +spread and impact of the COVID-19 pandemic in the United States. To date, the +survey has collected more than 50 million responses. In this post, we show how +the data from the {{< reflink "surveys" "COVID-19 survey" >}} +can be used to provide a broader picture of how American’s risk behaviors and +sentiments amidst a global pandemic.

+

All of the above plots were built using aggregate data for the United States +that CMU/Delphi Group & Facebook provide to the public through the {{< apireflink "symptom-survey/" "COVIDcast Epidata API" >}}, and +visualize in the {{< reflink "/covidcast" "Delphi Group’s survey dashboard" >}}. Public, aggregate data for the +global COVID-19 survey can be accessed via University of Maryland’s +API. We encourage researchers, public health +officials, and the public to use the survey data and tools for their own +analyses. Microdata is also available upon +request +to academic and nonprofit researchers under data license agreements.

+
diff --git a/content/covidcast/surveys.md b/content/covidcast/surveys.md index 63cd975d1..fcf64e2f6 100644 --- a/content/covidcast/surveys.md +++ b/content/covidcast/surveys.md @@ -69,9 +69,9 @@ Getting access to survey data for research: [complete this form](https://datafor ### Media inquiries: -[Byron Spice](mailto:bspice@cs.cmu.edu) -Director, Media Relations -School of Computer Science +[Stacy Kish](mailto:skish@andrew.cmu.edu) +Associate Director, Research Communications +Dietrich College Carnegie Mellon University ### All other questions: diff --git a/data/authors.yaml b/data/authors.yaml index 47aff9d34..924e7669e 100644 --- a/data/authors.yaml +++ b/data/authors.yaml @@ -38,6 +38,12 @@ name: Larry Wasserman link: http://www.stat.cmu.edu/~larry/ description: is a Professor in the Department of Statistics & Data Science at CMU as well as in the Machine Learning Department and is a member of Delphi. +- key: lmorinishi + name: Leanna Morinishi + description: is a data scientist on the Physical Modeling team at Facebook. +- key: kbarkume + name: Kris Barkume + description: is a research scientist on the Physical Modeling team at Facebook - key: hzhou name: Helen Zhou link: https://www.helen-zhou.com diff --git a/package-lock.json b/package-lock.json index 3f7527ed4..99650b431 100644 --- a/package-lock.json +++ b/package-lock.json @@ -1,6 +1,6 @@ { "name": "www-main", - "version": "1.12.5", + "version": "1.12.6", "lockfileVersion": 1, "requires": true, "dependencies": { diff --git a/package.json b/package.json index b82f7d86a..0dbbbb648 100644 --- a/package.json +++ b/package.json @@ -1,6 +1,6 @@ { "name": "www-main", - "version": "1.12.5", + "version": "1.12.6", "private": true, "dependencies": { "@fortawesome/fontawesome-free": "^5.15.1", diff --git a/static/blog/2021-01-22-holiday-surveys_files/figure-html/spent-time-1.svg b/static/blog/2021-01-22-holiday-surveys_files/figure-html/spent-time-1.svg new file mode 100644 index 000000000..75e7cc152 --- /dev/null +++ b/static/blog/2021-01-22-holiday-surveys_files/figure-html/spent-time-1.svg @@ -0,0 +1,102 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +25 +30 +35 +40 + + + + + + + + +Nov 16 2020 +Nov 30 2020 +Dec 14 2020 +Dec 28 2020 +Date +% spent time with non-household member in past 24h + +Region + + + + + + + + +Midwest +Northeast +South +West +7-day rolling average +Percent surveyed that spent time with a non-household member +Data from Delphi COVIDcast, delphi.cmu.edu + diff --git a/static/blog/2021-01-22-holiday-surveys_files/figure-html/tested-recently-1.svg b/static/blog/2021-01-22-holiday-surveys_files/figure-html/tested-recently-1.svg new file mode 100644 index 000000000..bee06edd9 --- /dev/null +++ b/static/blog/2021-01-22-holiday-surveys_files/figure-html/tested-recently-1.svg @@ -0,0 +1,98 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +-20 +0 +20 + + + + + + + +Nov 16 2020 +Nov 30 2020 +Dec 14 2020 +Dec 28 2020 +Date +% tested in past 14 days + +Region + + + + + + + + +Midwest +Northeast +South +West +7-day rolling average +Percent surveyed that were tested recently +Data from Delphi COVIDcast, delphi.cmu.edu + diff --git a/static/blog/2021-01-22-holiday-surveys_files/figure-html/traveled-recently-1.svg b/static/blog/2021-01-22-holiday-surveys_files/figure-html/traveled-recently-1.svg new file mode 100644 index 000000000..30ef3d543 --- /dev/null +++ b/static/blog/2021-01-22-holiday-surveys_files/figure-html/traveled-recently-1.svg @@ -0,0 +1,750 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +-20 +0 +20 + + + + + + + +Nov 16 2020 +Nov 30 2020 +Dec 14 2020 +Dec 28 2020 +Date +% traveled out-of-state in last 5 days + +Region + + + + + + + + +Midwest +Northeast +South +West +From Delphi's surveys, conducted through Facebook +Relative 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