Changes in emergency department utilisation in Germany before and during different phases of the COVID-19 pandemic, using data from a national surveillance system up to June 2021.

BACKGROUND: During the COVID-19 pandemic and associated public health and social measures, decreasing patient numbers have been described in various healthcare settings in Germany, including emergency care. This could be explained by changes in disease burden, e.g. due to contact restrictions, but could also be a result of changes in utilisation behaviour of the population. To better understand those dynamics, we analysed routine data from emergency departments to quantify changes in consultation numbers, age distribution, disease acuity and day and hour of the day during different phases of the COVID-19 pandemic. METHODS: We used interrupted time series analyses to estimate relative changes for consultation numbers of 20 emergency departments spread throughout Germany. For the pandemic period (16-03-2020 - 13-06-2021) four different phases of the COVID-19 pandemic were defined as interruption points, the pre-pandemic period (06-03-2017 - 09-03-2020) was used as the reference. RESULTS: The most pronounced decreases were visible in the first and second wave of the pandemic, with changes of - 30.0% (95%CI: - 32.2%; - 27.7%) and - 25.7% (95%CI: - 27.4%; - 23.9%) for overall consultations, respectively. The decrease was even stronger for the age group of 0-19 years, with - 39.4% in the first and - 35.0% in the second wave. Regarding acuity levels, consultations assessed as urgent, standard, and non-urgent showed the largest decrease, while the most severe cases showed the smallest decrease. CONCLUSIONS: The number of emergency department consultations decreased rapidly during the COVID-19 pandemic, without extensive variation in the distribution of patient characteristics. Smallest changes were observed for the most severe consultations and older age groups, which is especially reassuring regarding concerns of possible long-term complications due to patients avoiding urgent emergency care during the pandemic.

Sustaining surveillance as an intervention during the COVID-19 pandemic in Cabo Verde and implications for malaria elimination.

Cabo Verde reported the first case of COVID-19 on March 19, 2020. Containment measures were quickly implemented and over 80,000 COVID-19 tests were performed in 2020 with 11,840 confirmed infections (2% of the population) and 154 deaths. In a setting where the last locally acquired malaria case was reported in January 2018, any interruptions to malaria care-seeking have the potential for infections to go untreated and transmission re-establishing. This work aims to determine whether there was any change in the number of people seeking care or being tested for malaria and, using an interrupted time series analysis, identify if any change was associated with implemented COVID-19 measures. Routinely collected surveillance data for outpatient visits, testing for malaria and COVID-19 were aggregated by month for each health facility (outpatient and malaria) or by municipality (COVID-19) from 2017 through 2020. The timeline of COVID-19 measures was generated based on when and where they were implemented. Results show that there was a marked shift in care-seeking in Cabo Verde. Overall, the mean number of observed outpatient visits decreased from 2,057 visits per month during 2017-2019 to 1,088 in 2020, an estimated 28% reduction. However, malaria testing rates per 1,000 outpatient visits after the pandemic began increased by 8% compared to expected trends. Results suggest that the pandemic impacted care-seeking but led to a non-significant increase in testing for malaria per 1,000 outpatient visits. With the cessation of international travel, the risk of imported infections seeding new transmission declined suggesting the risk of undetected transmission was low. It is important for countries to understand their specific malaria risks and vulnerabilities in order to ensure that any progress towards the interruption of malaria transmission can be sustained.

Infodemic Preparedness and COVID-19: Searching about Public Health and Social Measures Is Associated with Digital Health Literacy in University Students.

We aimed to evaluate the associations between information searching about public health and social measures (PHSM) and university students' digital health literacy (DHL) related to the new coronavirus (SARS-CoV-2) and COVID-19. METHODS: This cross-sectional study included 3,084 Portuguese university students (75.7% females), with an average age of 24.2 (SD = 7.5). Sociodemographic data, DHL questionnaire and online information concerning PHSM were gathered. Cox proportional hazards models were performed. RESULTS: Students who searched for personal protective measures achieved in shorter time sufficient "evaluating reliability" (HR = 1.4; 95% CI = 1.1; 1.7) and "determining relevance" (HR = 1.5; 95% CI = 1.2; 1.8). Searching for surveillance and response measures was associated with sufficient "determining relevance" (HR = 1.4; 95% CI = 1.1; 1.9). Finally, those students who searched for environmental, economic and psychosocial measures achieved in shorter time "determining relevance" (HR = 1.2; 95% CI = 1.0; 1.4). CONCLUSIONS: Searching for PHSM was significantly associated with an increased likelihood of achieving sufficient DHL subscales in a shorter time. Further studies are needed, including developing strategies to increase the availability of high-quality information concerning public health and social measures and to improve (digital) health literacy.

Non-pharmaceutical intervention levels to reduce the COVID-19 attack ratio among children.

The attack ratio in a subpopulation is defined as the total number of infections over the total number of individuals in this subpopulation. Using a methodology based on an age-stratified transmission dynamics model, we estimated the attack ratio of COVID-19 among children (individuals 0-11 years) when a large proportion of individuals eligible for vaccination (age 12 and above) are vaccinated to contain the epidemic among this subpopulation, or the effective herd immunity (with additional physical distancing measures). We describe the relationship between the attack ratio among children, the time to remove infected individuals from the transmission chain and the children-to-children daily contact rate while considering the increased transmissibility of virus variants (using the Delta variant as an example). We illustrate the generality and applicability of the methodology established by performing an analysis of the attack ratio of COVID-19 among children in the population of Canada and in its province of Ontario. The clinical attack ratio, defined as the number of symptomatic infections over the total population, can be informed from the attack ratio and both can be reduced substantially via a combination of reduced social mixing and rapid testing and isolation of the children.

Psychosocial determinants of adherence to public health and social measures (PHSMs) in 18 African Union Member States during the early phase of the COVID-19 pandemic: results of a cross-sectional survey.

OBJECTIVE: The objective of this study was to gain a better understanding of the psychosocial and sociodemographic factors that affected adherence to COVID-19 public health and social measures (PHSMs), and to identify the factors that most strongly related to whether citizens followed public health guidance. DESIGN: Cross-sectional study. SETTING AND PARTICIPANTS: Nationally representative telephone surveys were conducted from 4-17 August 2020 in 18 African Union Member States. A total of 21 600 adults (mean age=32.7 years, SD=11.4) were interviewed (1200 in each country). OUTCOME MEASURES: Information including sociodemographics, adherence to PHSMs and psychosocial variables was collected. Logistic regression models examined the association between PHSM adherence (eg, physical distancing, gathering restrictions) and sociodemographic and psychosocial characteristics (eg, risk perception, trust). Factors affecting adherence were ranked using the Shapley regression decomposition method. RESULTS: Adherence to PHSMs was high, with better adherence to personal than community PHSMs (65.5% vs 30.2%, p<0.05). Psychosocial measures were significantly associated with personal and community PHSMs (p<0.05). Women and older adults demonstrated better adherence to personal PHSMs (adjusted OR (aOR): women=1.43, age=1.01, p<0.05) and community PHSMs (aOR: women=1.57, age=1.01, p<0.05). Secondary education was associated with better adherence only to personal PHSMs (aOR=1.22, p<0.05). Rural residence and access to running water were associated with better adherence to community PHSMs (aOR=1.12 and 1.18, respectively, p<0.05). The factors that most affected adherence to personal PHSMs were: self-efficacy; trust in hospitals/health centres; knowledge about face masks; trust in the president; and gender. For community PHSMs they were: gender; trust in the president; access to running water; trust in hospitals/health centres; and risk perception. CONCLUSIONS: Psychosocial factors, particularly trust in authorities and institutions, played a critical role in PHSM adherence. Adherence to community PHSMs was lower than personal PHSMs since they can impose significant burdens, particularly on the socially vulnerable.

Assessment of Traffic Accidents in Japan during the COVID-19 Pandemic vs. Previous Years: A Preliminary Report.

Beginning in April 2020, social distancing measures were implemented to mitigate the COVID-19 pandemic in Japan. We assessed whether traffic accident rates had decreased from April 2020 to December 2021 as compared with previous years. The analysis included 2,934,477 traffic accidents, and the trend of decreasing rates of traffic accidents in recent years and seasonal fluctuations in traffic accidents were considered. The yearly change in the traffic accident rate between 2015 and 2019 was estimated, and the traffic accident rate in 2020 and 2021 was predicted. This was followed by the comparison of observed vs. predicted traffic accident rate. In 2020, the observed vs. expected rates of traffic accidents were lower in April to December 2020, and the rate of traffic accidents in Japan was 30-40% lower in April-May 2020 than would be expected based on trends from previous years. In 2021, rates of traffic accidents remained lower than expected between January and November, but the magnitude of decrease was not as pronounced. These findings could be explained by social distancing policies, including the declaration of the state of emergency, and the relaxation of public health and social measures over time.

A Novel Approach on Deep Learning-Based Decision Support System Applying Multiple Output LSTM-Autoencoder: Focusing on Identifying Variations by PHSMs' Effect over COVID-19 Pandemic.

Following the outbreak of the COVID-19 pandemic, the continued emergence of major variant viruses has caused enormous damage worldwide by generating social and economic ripple effects, and the importance of PHSMs (Public Health and Social Measures) is being highlighted to cope with this severe situation. Accordingly, there has also been an increase in research related to a decision support system based on simulation approaches used as a basis for PHSMs. However, previous studies showed limitations impeding utilization as a decision support system for policy establishment and implementation, such as the failure to reflect changes in the effectiveness of PHSMs and the restriction to short-term forecasts. Therefore, this study proposes an LSTM-Autoencoder-based decision support system for establishing and implementing PHSMs. To overcome the limitations of existing studies, the proposed decision support system used a methodology for predicting the number of daily confirmed cases over multiple periods based on multiple output strategies and a methodology for rapidly identifying varies in policy effects based on anomaly detection. It was confirmed that the proposed decision support system demonstrated excellent performance compared to models used for time series analysis such as statistical models and deep learning models. In addition, we endeavored to increase the usability of the proposed decision support system by suggesting a transfer learning-based methodology that can efficiently reflect variations in policy effects. Finally, the decision support system proposed in this study provides a methodology that provides multi-period forecasts, identifying variations in policy effects, and efficiently reflects the effects of variation policies. It was intended to provide reasonable and realistic information for the establishment and implementation of PHSMs and, through this, to yield information expected to be highly useful, which had not been provided in the decision support systems presented in previous studies.

Behavioral factors associated with SARS-CoV-2 infection in Japan.

BACKGROUND: The relative burden of COVID-19 has been less severe in Japan. One reason for this may be the uniquely strict restrictions imposed upon bars/restaurants. To assess if this approach was appropriately targeting high-risk individuals, we examined behavioral factors associated with SARS-CoV-2 infection in the community. METHODS: This multicenter case-control study involved individuals receiving SARS-CoV-2 testing in June-August 2021. Behavioral exposures in the past 2 weeks were collected via questionnaire. SARS-CoV-2 PCR-positive individuals were cases, while PCR-negative individuals were controls. RESULTS: The analysis included 778 individuals (266 [34.2%] positives; median age [interquartile range] 33 [27-43] years). Attending three or more social gatherings was associated with SARS-CoV-2 infection (adjusted odds ratio [aOR] 2.00 [95% CI 1.31-3.05]). Attending gatherings with alcohol (aOR 2.29 [1.53-3.42]), at bars/restaurants (aOR 1.55 [1.04-2.30]), outdoors/at parks (aOR 2.87 [1.01-8.13]), at night (aOR 2.07 [1.40-3.04]), five or more people (aOR 1.81 [1.00-3.30]), 2 hours or longer (aOR 1.76 [1.14-2.71]), not wearing a mask during gatherings (aOR 4.18 [2.29-7.64]), and cloth mask use (aOR 1.77 [1.11-2.83]) were associated with infection. Going to karaoke (aOR 2.53 [1.25-5.09]) and to a gym (aOR 1.87 [1.11-3.16]) were also associated with infection. Factors not associated with infection included visiting a cafe with others, ordering takeout, using food delivery services, eating out by oneself, and work/school/travel-related exposures including teleworking. CONCLUSIONS: We identified multiple behavioral factors associated with SARS-CoV-2 infection, many of which were in line with the policy/risk communication implemented in Japan. Rapid assessment of risk factors can inform decision making.

The COVID-19 pandemic in the WHO African region: the first year (February 2020 to February 2021).

The World Health Organization African region recorded its first laboratory-confirmed coronavirus disease-2019 (COVID-19) cases on 25 February 2020. Two months later, all the 47 countries of the region were affected. The first anniversary of the pandemic occurred in a changed context with the emergence of new variants of concern (VOC) and growing COVID-19 fatigue. This study describes the epidemiological trajectory of COVID-19 in the region, summarises public health and social measures (PHSM) implemented and discusses their impact on the pandemic trajectory. As of 24 February 2021, the African region accounted for 2.5% of cases and 2.9% of deaths reported globally. Of the 13 countries that submitted detailed line listing of cases, the proportion of cases with at least one co-morbid condition was estimated at 3.3% of all cases. Hypertension, diabetes and human immunodeficiency virus (HIV) infection were the most common comorbid conditions, accounting for 11.1%, 7.1% and 5.0% of cases with comorbidities, respectively. Overall, the case fatality ratio (CFR) in patients with comorbid conditions was higher than in patients without comorbid conditions: 5.5% vs. 1.0% (P < 0.0001). Countries started to implement lockdown measures in early March 2020. This contributed to slow the spread of the pandemic at the early stage while the gradual ease of lockdowns from 20 April 2020 resulted in an upsurge. The second wave of the pandemic, which started in November 2020, coincided with the emergence of the new variants of concern. Only 0.08% of the population from six countries received at least one dose of the COVID-19 vaccine. It is critical to not only learn from the past 12 months to improve the effectiveness of the current response but also to start preparing the health systems for subsequent waves of the current pandemic and future pandemics.

Superiority of Mild Interventions against COVID-19 on Public Health and Economic Measures.

(1) Background: During the global spread of COVID-19, Japan has been among the top countries to maintain a relatively low number of infections, despite implementing limited institutional interventions and its high population density. This study investigated how limited intervention policies have affected public health and economic conditions in the COVID-19 context and aimed to gain insight into the effective and sustainable measures against new infectious diseases in densely inhabited areas. (2) Methods: A system dynamics approach was employed. Qualitative causal loop analysis and stock and quantitative flow model analysis were performed, using a Tokyo Metropolitan area dataset. (3) Results: A causal loop analysis suggested that there were risks in prematurely terminating such interventions. Based on this result and the subsequent quantitative modeling, we found that the short-term effectiveness of a short-term pre-emptive stay-at-home request caused a resurgence in the number of positive cases, whereas an additional request provided a limited negative add-on effect for economic measures (e.g., number of electronic word-of-mouth communications and restaurant visits). (4) Conclusions: These findings suggest the superiority of a mild and continuous intervention as a long-term countermeasure under epidemic pressures when compared with strong intermittent interventions.

Early COVID-19 pandemic's toll on tuberculosis services, WHO European Region, January to June 2020.

BackgroundEssential health services, including for tuberculosis (TB), are being affected by public health and social measures (PHSM) introduced to control COVID-19. In many settings, TB resources, facilities and equipment are being redirected towards COVID-19 response.AimWe sought to assess the COVID-19 pandemic's impact on TB services in the World Health Organization (WHO) European Region.MethodsThe fifty-three European Region Member States were asked to report qualitative and quantitative data in quarter one and two (Q1 and Q2) 2020. TB notifications were triangulated with the severity score on domestic movement restrictions to assess how they may have influenced TB detection.ResultsTwenty-nine countries reported monthly TB notifications for the first half of 2019 and 2020. TB notifications decreased by 35.5% during Q2 2020 compared with Q2 2019, which is six-fold more than the average annual decrease of 5.1% documented during 2015-2019. The number of patients enrolled in rifampicin-resistant/multidrug-resistant TB treatment also decreased dramatically in Q2 2020, by 33.5%. The highest movement restriction severity score was observed between April and May 2020, which coincided with the highest observed decrease in TB notifications.ConclusionA decrease in TB detection and enrolment to treatment may cause increases in TB burden and threatens the Region's ability to reach the TB targets of the 2030 Sustainable Development Goals, still this might be mitigated with rapid restoration of TB services and the implementation of targeted interventions during periods with severe PHSM in place, such as those introduced in response to the COVID-19 pandemic.

A comparative study of public health and social measures of COVID-19 advocated in different countries.

Coronavirus 2019 (COVID-19) has had a significant impact on the world. Different countries introduced various public health and social measures (PHSMs) against the coronavirus. This paper aims to (a) examine how national policies on PHSMs were framed and which PHSMs were adopted; (b) compare the similarities and differences of PHSMs advocated by different countries; and (c) examine whether these measures have changed with time. We performed a content analysis of 160 COVID-19 policy documents on the websites of the WHO and ten countries' government websites on COVID-19 between December 1, 2019 and May 31, 2020. Results showed that although the initial responses to COVID-19 in different countries varied, there was a homogenization of PHSMs over time: by May 31, 2020, almost all the countries we studied implemented the major PHSMs that the WHO recommended, except Sweden, which applied only part of the major PHSMs recommended by the WHO. The differences among countries were in the speediness, strictness and resourcefulness of the PHSMs implementation. We suggest that a timely and effective utilization of the integrated package of health measures with the support of adequate resources may help the efficient implementation of PHSMs.

On-site Dining in Tokyo During the COVID-19 Pandemic: Time Series Analysis Using Mobile Phone Location Data.

BACKGROUND: During the second wave of COVID-19 in August 2020, the Tokyo Metropolitan Government implemented public health and social measures to reduce on-site dining. Assessing the associations between human behavior, infection, and social measures is essential to understand achievable reductions in cases and identify the factors driving changes in social dynamics. OBJECTIVE: The aim of this study was to investigate the association between nighttime population volumes, the COVID-19 epidemic, and the implementation of public health and social measures in Tokyo. METHODS: We used mobile phone location data to estimate populations between 10 PM and midnight in seven Tokyo metropolitan areas. Mobile phone trajectories were used to distinguish and extract on-site dining from stay-at-work and stay-at-home behaviors. Numbers of new cases and symptom onsets were obtained. Weekly mobility and infection data from March 1 to November 14, 2020, were analyzed using a vector autoregression model. RESULTS: An increase in the number of symptom onsets was observed 1 week after the nighttime population volume increased (coefficient=0.60, 95% CI 0.28 to 0.92). The effective reproduction number significantly increased 3 weeks after the nighttime population volume increased (coefficient=1.30, 95% CI 0.72 to 1.89). The nighttime population volume increased significantly following reports of decreasing numbers of confirmed cases (coefficient=-0.44, 95% CI -0.73 to -0.15). Implementation of social measures to restaurants and bars was not significantly associated with nighttime population volume (coefficient=0.004, 95% CI -0.07 to 0.08). CONCLUSIONS: The nighttime population started to increase after decreasing incidence of COVID-19 was announced. Considering time lags between infection and behavior changes, social measures should be planned in advance of the surge of an epidemic, sufficiently informed by mobility data.