Population density
Others warned that easing social distancing restrictions should be considered carefully, as small increases in contact rates are likely to risk resurgence. 17 This study showed that incidence rates strongly decreased in most densely populated areas. However, given the ecological nature of the data (aggregated to UTLA-level), one cannot infer associations for individual patients.įlaxman et al concluded that social distancing measures had an impact on reducing the transmission of COVID-19. The study’s longitudinal approach allowed the comparison of incidence rates over time, and the association of population density with changes in incidence rates. Although adherence to these distancing rules seems high, 14 it is unknown whether there is a relationship between adherence and population density. This may strengthen the conclusion that social distancing resulted in the strongest decrease in incidence rate in most densely populated areas. 13 Given the time-lag between being infected and tested, the calculated incidence rates per 100 000 people might therefore rather be an indication of the spreading of the virus in the previous week. The lab-confirmed cases on the PHE Dashboard are patients who had probably been infected about a week before their test, as the median incubation period is 5–6 days. Since this testing policy changed at the end of April, this longitudinal study used available data until April 20 to avoid measurement bias in the calculation of weekly COVID-19 incidence rates. 12 As a result, the lab-confirmed cases on the PHE Dashboard are probably an underestimation of the true number of COVID-19 cases, but testing practices should have been the same everywhere in England. The UK government’s central policy prioritised specific people to be tested. The potential confounders and covariates were standardised around the mean.
![population density population density](https://2.bp.blogspot.com/-VAF8Geq__HI/UKvQQengR3I/AAAAAAAAADk/uP4Z7qL5K4E/s1600/population+density.jpg)
Population density was divided into quartiles: quartile 1 was the least densely populated UTLAs, and quartile 4 the most densely populated ULTAs. The multivariable model included an interaction between weeks and population density. Time was the level-1 unit and UTLA the level-2 unit, resulting in 745 observations in the model. Linking these data to the weekly regional COVID-19 incidence rates per 100 000 people allowed the association of population density with changes in weekly regional COVID-19 incidence rates per 100 000 people.Ī multilevel model was used to analyse repeated measurements 11 for the following weeks: March 16–22, March 23–29, March 30-April 5, April 6–12, and April 13–19. The Office for National Statistics 3 provides relevant data for each of the 149 UTLAs: percentage aged ≥65 years, percentage non-white British, percentage in two highest classes of the National Statistics Socioeconomic Classification, male life expectancy at birth, and number of people per square kilometre (see Supplementary Table S1 for descriptive statistics).
![population density population density](https://i.pinimg.com/736x/fc/9b/f5/fc9bf51d9fcb2c3da81c2fcfc3bb35b9.jpg)
7 Population characteristics included as co-variates are d) healthier populations, and e) the COVID-19 prevalence rate per 100 000 people on March 15. To explore the spreading of COVID-19 in relation to population density, this study included potential confounding population characteristics: a) older age, as older people are said to be more susceptibility to COVID-19 6 and are more likely to live in less densely populated areas 7 b) ethnicity, as ethnic minorities are overrepresented among COVID-19 cases 8, 9 and are more likely to live in more densely populated areas 7 c) higher occupational classes, as these people may have more flexible work arrangements, allowing them to better cope with the restrictions, 10 and are more likely to live in cities. Adding UTLAs’ population sizes 5 to this datafile allowed the calculation of weekly regional incidence rates per 100 000 people.
![population density population density](https://live.staticflickr.com/6162/6172038745_0c8a49ff2a_b.jpg)
4 This study used lab-confirmed cases for 16 March–19 April. Data were downloaded at the beginning of May, with the notion that only data from 5 days or more ago can be considered complete. Public Health England (PHE) Dashboard provides daily cumulative counts of lab-confirmed COVID-19 cases for each of the 149 UTLAs that is, the highest (unitary) tier of local government: London and metropolitan boroughs, and unitary districts in shire counties.