Age, Gender, and Disease as Determinants of Social Distancing: Germany as a Case Study.

A mix of guidance and mandated regulations during the coronavirus disease (COVID-19) pandemic served to reduce the number of social contacts, to ensure distancing in public spaces, and to maintain the isolation of infected individuals. Individual variation in compliance to social distancing in Germany, relating to age, gender, or the presence of pre-existing health conditions, was examined using results from a total of 39 375 respondents to a web-based behavioral survey.Older people and females were more willing to engage in social distancing. Those with chronic conditions showed overall higher levels of compliance, but those with cystic fibrosis, human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS), and epilepsy showed less adherence to general social distancing measures but were significantly more likely to isolate in their homes. Behavioral differences partly lie in the nature of each condition, especially with those conditions likely to be exacerbated by COVID-19. Compliance differences for age and gender are largely in line with previous studies.

Internet searching on the head louse in the UK since the COVID-19 pandemic.

BACKGROUND: Wide-ranging restrictions on social and educational activities were imposed in 2020 in response to the COVID-19 pandemic. These likely influenced the population dynamics of the head louse. Close physical contact between human hosts is required for transmission of this ectoparasite. METHOD: Pre- and post-pandemic internet interest in the head louse in the UK was compared using Google Trends data from March 2017 to March 2022 and modeling using the Meta Prophet package. The influence of school holidays and school attendance was also investigated. RESULTS: There was a sharp decline in internet searching of the term "head louse" from March 2020 onwards coinciding with COVID-19 restrictions, and a large difference between pre- and post-pandemic search volumes. No influence of school holidays or attendance on internet searching on the head louse was found. CONCLUSION: The results suggest pandemic restrictions have had a large effect on head louse incidence.

Mobility and COVID-19 mortality across Scandinavia: A modeling study.

BACKGROUND: In response to COVID-19, the Swedish government imposed few travel and mobility restrictions. This contrasted with its Scandinavian neighbours which implemented stringent restrictions. The influence these different approaches had on mobility, and thus on COVID-19 mortality was investigated. METHODS: Datasets indicating restriction severity and community mobility were examined; Google's 'Community Movement Reports' (CMR) show activity at key location categories; the Oxford COVID-19 Government Response Tracker collates legislative restrictions into a 'Stringency Index' (SI). RESULTS: CMR mobility categories were negatively correlated with COVID-19 mortality. The strongest correlations were obtained by negatively time lagging mortality data, suggesting restrictions had a delayed influence. During the 'first wave' a model using SI (AIC 632.87) proved favorable to one using contemporaneous CMR data and SI (AIC 1193.84), or lagged CMR data and SI (AIC 642.35). Validation using 'second wave' data confirmed this; the model using SI solely again being optimal (RMSE: 0.2486 vs. 0.522 and 104.62). Cross-country differences were apparent in all models; Swedish data, independent of SI and CMR, proved significant throughout. There was a significant association for Sweden and the death number across models. CONCLUSION: SI may provide a broader, more accurate, representation of changes in movement in response to COVID-19 restrictions.

The Relationship between Mobility and COVID-19 in Germany: Modeling Case Occurrence using Apple's Mobility Trends Data.

BACKGROUND: Restrictions on social interaction and movement were implemented by the German government in March 2020 to reduce the transmission of coronavirus disease 2019 (COVID-19). Apple's "Mobility Trends" (AMT) data details levels of community mobility; it is a novel resource of potential use to epidemiologists. OBJECTIVE: The aim of the study is to use AMT data to examine the relationship between mobility and COVID-19 case occurrence for Germany. Is a change in mobility apparent following COVID-19 and the implementation of social restrictions? Is there a relationship between mobility and COVID-19 occurrence in Germany? METHODS: AMT data illustrates mobility levels throughout the epidemic, allowing the relationship between mobility and disease to be examined. Generalized additive models (GAMs) were established for Germany, with mobility categories, and date, as explanatory variables, and case numbers as response. RESULTS: Clear reductions in mobility occurred following the implementation of movement restrictions. There was a negative correlation between mobility and confirmed case numbers. GAM using all three categories of mobility data accounted for case occurrence as well and was favorable (AIC or Akaike Information Criterion: 2504) to models using categories separately (AIC with "driving," 2511. "transit," 2513. "walking," 2508). CONCLUSION: These results suggest an association between mobility and case occurrence. Further examination of the relationship between movement restrictions and COVID-19 transmission may be pertinent. The study shows how new sources of online data can be used to investigate problems in epidemiology.

WITHDRAWN.

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