Infectious Disease Preparedness for Homeless Populations: Recommendations from a Community-Academic Partnership.

BACKGROUND: People experiencing homelessness are at increased risk of infectious disease transmission due to congregate living conditions, barriers to healthcare, and excess burden of underlying chronic disease. OBJECTIVES: We are a multisectoral community-academic partnership working to address the intersecting crises of homelessness and health disparities in Tippecanoe County, Indiana. We offer key recommendations for infectious disease preparedness and risk mitigation for homeless populations based on our ongoing community-based participatory research and lessons learned through COVID-19 response and Monkeypox preparations. LESSONS LEARNED: Infectious disease preparedness and response in homeless populations requires strong local partnerships; ongoing training and support for staff and volunteers of homeless shelters and service agencies; tailored outreach, education, and communication with people experiencing homelessness; and standardized processes for creating, disseminating, enforcing, and evaluating public health policies in homeless shelters. Consistency and open communication are key to a successful community-academic partnership. CONCLUSIONS: Community-academic partnerships are critical to effective infectious disease preparedness in homeless populations. The lessons learned from community-based participatory research with homeless communities and multisectoral partners on the frontline can improve future outbreak and pandemic response for people experiencing homelessness and other vulnerable communities in the United States.

Is COVID-19 as Lethal as the Spanish Flu? The Australian Experience in 1919 and 2020 and the Role of Nonpharmaceutical Interventions (NPIs).

We conducted a comparative historical study to interrogate Professor Peter Doherty's warning to Australians in April 2020 that 'COVID-19 is just as lethal as the Spanish flu'. We identified the epicentres of both pandemics, namely, metropolitan Sydney in 1919 and metropolitan Melbourne in 2020 and compared the lethality of the Spanish Flu and COVID-19 in these two cities. Lethality was measured by the number and rate of hospital admissions, death rates, age-specific death rates and age-standardised mortality rates (ASMRs). Using these measures, we demonstrated the strikingly different waves of infection, their severity at various points in time and the cumulative impact of the viruses by the end of our study period, i.e., 30 September in 1919 and 2020. Hospital admissions and deaths from the Spanish Flu in 1919 were more than 30 times higher than those for COVID-19 in 2020. The ASMR per 100,000 population for the Spanish Flu was 383 compared to 7 for COVID-19: The former was about 55 times higher than the latter. These results suggest that the Spanish Flu was more lethal than COVID-19. Professor Doherty's warning was perhaps taken seriously and that partly explains the findings of this study. Containing infection in 1919 and 2020 threw the burden on nonpharmaceutical interventions (NPIs) such as 'protective sequestration' (quarantine), contact tracing, lockdowns and masks. It is likely that the persistent and detailed contact tracing scheme provides the best possible explanation for why NPIs in 2020 were more effective than in 1919 and therefore contributed to the lower lethality of the COVID-19 pandemic in its first year.

Modeling COVID-19 spread using multi-agent simulation with small-world network approach.

BACKGROUND: The rapid global spread of COVID-19 has seriously impacted people's daily lives and the social economy while also posing a threat to their lives. The analysis of infectious disease transmission is of significant importance for the rational allocation of epidemic prevention and control resources, the management of public health emergencies, and the improvement of future public health systems. METHODS: We propose a spatiotemporal COVID-19 transmission model with a neighborhood as an agent unit and an urban spatial network with long and short edge connections. The spreading model includes a network of defined agent attributes, transformation rules, and social relations and a small world network representing agents' social relations. Parameters for each stage are fitted by the Runge-Kutta method combined with the SEIR model. Using the NetLogo development platform, accurate dynamic simulations of the spatial and temporal evolution of the early epidemic were achieved. RESULTS: Experimental results demonstrate that the fitted curves from the four stages agree with actual data, with only a 12.27% difference between the average number of infected agents and the actual number of infected agents after simulating 1 hundred times. Additionally, the model simulates and compares different "city closure" scenarios. The results showed that implementing a 'lockdown' 10 days earlier would lead to the peak number of infections occurring 7 days earlier than in the normal scenario, with a reduction of 40.35% in the total number of infections. DISCUSSION: Our methodology emphasizes the crucial role of timely epidemic interventions in curbing the spread of infectious diseases, notably in the predictive assessment and evaluation of lockdown strategies. Furthermore, this approach adeptly forecasts the influence of varying intervention timings on peak infection rates and total case numbers, accurately reflecting real-world virus transmission patterns. This highlights the importance of proactive measures in diminishing epidemic impacts. It furnishes a robust framework, empowering policymakers to refine epidemic response strategies based on a synthesis of predictive modeling and empirical data.

The impact of public transportation on the transmission of COVID-19 in Rwanda.

Introduction: The onset of the COVID-19 pandemic has placed a significant burden on healthcare systems worldwide, particularly in sub-Saharan regions where healthcare resources are limited. The transmission of SARS-CoV-2 is facilitated by the movement of people from place to place. Therefore, implementing measures that restrict movement of people and contacts is crucial in controlling the spread of the disease. Following the identification of the first COVID-19 case in Rwanda, the government implemented stringent measures, including a complete nationwide lockdown, border closures, curfews, reduced capacity in public transportation and businesses, and mandatory testing. This study aims to assess epidemiological trends in COVID-19 cases in relation to changes in population mobility within the public transportation system. Methods: A descriptive analysis using publicly available data on COVID-19 epidemiological indicators (cases, deaths, vaccinations, and stringency index) and mobility data was conducted. Results: The results reveal a strong correlation between mobility in public transportation and other activities, underscoring Rwanda's reliance on its public transportation system. The study also identifies a pattern where increases in transit station mobility preceded spikes in COVID-19 cases, suggesting that the subsequent rise in public transportation usage may contribute to higher infection rates. Discussion: Therefore, this study emphasizes the importance of ongoing vigilance and regulatory measures regarding public transportation during infectious disease outbreaks.

Quality assessment and community detection methods for anonymized mobility data in the Italian Covid context.

We discuss how to assess the reliability of partial, anonymized mobility data and compare two different methods to identify spatial communities based on movements: Greedy Modularity Clustering (GMC) and the novel Critical Variable Selection (CVS). These capture different aspects of mobility: direct population fluxes (GMC) and the probability for individuals to move between two nodes (CVS). As a test case, we consider movements of Italians before and during the SARS-Cov2 pandemic, using Facebook users' data and publicly available information from the Italian National Institute of Statistics (Istat) to construct daily mobility networks at the interprovincial level. Using the Perron-Frobenius (PF) theorem, we show how the mean stochastic network has a stationary population density state comparable with data from Istat, and how this ceases to be the case if even a moderate amount of pruning is applied to the network. We then identify the first two national lockdowns through temporal clustering of the mobility networks, define two representative graphs for the lockdown and non-lockdown conditions and perform optimal spatial community identification on both graphs using the GMC and CVS approaches. Despite the fundamental differences in the methods, the variation of information (VI) between them assesses that they return similar partitions of the Italian provincial networks in both situations. The information provided can be used to inform policy, for example, to define an optimal scale for lockdown measures. Our approach is general and can be applied to other countries or geographical scales.

The effect of nonpharmaceutical interventions on influenza virus transmission.

Background: The use of nonpharmaceutical interventions (NPIs) during severe acute respiratory syndrome 2019 (COVID-19) outbreaks may influence the spread of influenza viruses. This study aimed to evaluate the impact of NPIs against SARS-CoV-2 on the epidemiological features of the influenza season in China. Methods: We conducted a retrospective observational study analyzing influenza monitoring data obtained from the China National Influenza Center between 2011 and 2023. We compared the changes in influenza-positive patients in the pre-COVID-19 epidemic, during the COVID-19 epidemic, and post-COVID-19 epidemic phases to evaluate the effect of NPIs on influenza virus transmission. Results: NPIs targeting COVID-19 significantly suppressed influenza activity in China from 2019 to 2022. In the seventh week after the implementation of the NPIs, the number of influenza-positive patients decreased by 97.46% in southern regions of China and 90.31% in northern regions of China. However, the lifting of these policies in December 2022 led to an unprecedented surge in influenza-positive cases in autumn and winter from 2022 to 2023. The percentage of positive influenza cases increased by 206.41% (p < 0.001), with high positivity rates reported in both the northern and southern regions of China. Conclusion: Our findings suggest that NPIs against SARS-CoV-2 are effective at controlling influenza epidemics but may compromise individuals' immunity to the virus.

Factors influencing operationalization of Integrated Disease Surveillance in Malawi.

OBJECTIVES: Malawi's disease surveillance system is built on several different data sources and systems and is informed by the Integrated Diseases Surveillance and Response (IDSR) strategy. This study was carried out as part of a larger multicountry study to identify context-specific factors, which influence the operationalization of integrated disease surveillance. STUDY DESIGN AND METHODS: A total of six focus group discussions were conducted with 43 relevant personnel at the primary and secondary healthcare levels in two districts (Lilongwe and Dowa) and at the national level. The discussions were analyzed and sorted into predefined categories based on the domains of the International Association of Public Health conceptual framework. RESULTS: We found ongoing efforts to enhance integrated disease surveillance operationalization, including the establishment of the Public Health Institute of Malawi for coordination, digitalizing the surveillance system through One Health Surveillance Platform, and improving communication among rapid response teams using WhatsApp. The adoption of World Health Organization's third edition IDSR technical guidelines was also underway. Nonetheless, there were major implementation barriers such as parallel and uncoordinated surveillance systems, priority conditions that cannot be diagnosed at the point of reporting, lack of case definitions and diagnostic codes for priority conditions, reporting forms with unexplained acronyms, illegible data sources, unstable electronic data transfers, inadequate supervision and training, poor enforcement of reporting from private health facilities, high reporting burden, and lack of and feedback to those reporting. CONCLUSIONS: The results fit well into the predefined categories used. The study reveals basic problems with the operationalization, tools, and reporting forms used for IDSR. These findings may have implications for practice and policy in Malawi and other countries where IDSR is the national strategy for surveillance.

A tale of lockdown policies on the transmission of COVID-19 within and between Chinese cities: A study based on heterogeneous treatment effect.

During the early outbreak phase of COVID-19 in China, lockdowns prevailed as the only available policy tools to mitigate the spread of infection. To evaluate the impact of lockdown policies in the context of the first phase of COVID-19 pandemic, we leverage data on daily confirmed cases per million people and related characteristics of a large set of cities. The study analyzed 369 Chinese cities, among which 188 implemented lockdowns of varying severity levels from January 23 to March 31, 2020. We use nationwide Baidu Mobility data to estimate the impact of lockdown policies on mitigating COVID-19 cases through reducing human mobility. We adopt a heterogeneous treatment effect model to quantify the effect of lockdown policies on containing confirmed case counts. Our results suggest that lockdowns substantially reduced human mobility, and larger reduction in mobility occurred within-city compared to between-city. The COVID-19 daily confirmed cases per million people decreased by 9% - 9.2% for every ten-percentage point fall in within-city travel intensity in t+7 timeframe. We also find that one city's lockdowns can effectively reduce the spillover cases of the traveler's destination cities. We find no evidence that stricter lockdowns are more effective at mitigating COVID-19 risks. Our findings provide practical insights about the effectiveness of NPI during the early outbreak phase of the unprecedented pandemic.

Mortality in Norway and Sweden during the COVID-19 pandemic 2020-22: A comparative study.

BACKGROUND: Norway and Sweden picked two different ways to mitigate the dissemination of the SARS-CoV-2 virus. Norway introduced the strictest lockdown in Europe with strict border controls and intense virus tracking of all local outbreaks while Sweden did not. That resulted in 477 COVID-19 deaths (Norway) and 9737 (Sweden) in 2020, respectively. METHODS: Weekly number of COVID-19 related deaths and total deaths for 2020-22 were collected as well as weekly number of deaths for 2015-19 which were used as controls when calculating excess mortality. During the first 12-18 months with high rate of virus transmission in the society, excess mortality rates were used as substitute for COVID-19 deaths. When excess mortality rates later turned negative because of mortality displacement, COVID-19 deaths adjusted for bias due to overreporting were used. RESULTS: There were 17521 COVID-19 deaths in Sweden and 4272 in Norway in the study period. The rate ratio (RR) of COVID-19 related deaths in Sweden vs. Norway to the end of week 43, 2022, was 2.11 (95% CI 2.05-2.19). RR of COVID-19 related deaths vs. excess number of deaths were 2.5 (Sweden) and 1.3 (Norway), respectively. RR of COVID-19 deaths in Sweden vs. Norway after adjusting for mortality displacement and lockdown, was 1.35 (95% CI 1.31-1.39), corresponding to saving 2025 life in Norway. If including all deaths in 2022, RR= 1.28 (95% CI 1.24-1.31). CONCLUSIONS: Both COVID-19 related mortality and excess mortality rates are biased estimates. When adjusting for bias, mortality differences declined over time to about 30% higher mortality in Sweden after 30 months with pandemics.

Characteristics associated with attitudes and behaviors towards mask wearing during the COVID-19 pandemic: The Trojan Pandemic Response Initiative.

BACKGROUND: Attitudes and behaviors towards mask wearing may influence the ability to reduce transmission of COVID-19 and other diseases. METHODS: University students, staff, and faculty (N = 9653) responded to an email invitation to complete electronic surveys (November 2021 and April 2022). Surveys included 19 items measuring attitudes and behaviors towards mask wearing from the Understanding America Study. Linear mixed models including variables for sex, age group, division, race and ethnicity, political affiliation, and history of COVID-19, were used to estimate the mean difference of the mean score for attitudes and behavior between Time 1 (November 2021) and Time 2 (April 2022). RESULTS: Participants were mostly female (62.1%), students (70.6%), White (39.5%) and Asian (34.7%). More than half identified their political affiliation as Democrat (65.5%). Characteristic variable-by-time interactions for difference in mean mask attitude scores difference were significant at Time 1 (T1) and Time 2 (T2) between Black and White participants (B = 0.18 (0.05), 95% CI: 0.07, 0.28, p = 0.001), Asian and White participants (B = 0.07 (0.02), 95% CI: 0.03-0.12, p = 0.001), participants with self-reported history of COVID-19 and no history of COVID-19 (B= -0.13 (0.02), 95% CI: -0.07, -0.18, p < 0.0001), females and males (B = 0.07 (0.02), 95% CI: 0.03, 0.11, p = 0.001), Republicans and Democrats (B= -0.18 (0.04), 95%CI: -0.26, -0.10, p < 0.0001) and Independents and Democrats (B= -0.10 (0.03), 95%CI: -0.15, -0.05, p < 0.0001). Mean difference in mean scores for mask behaviors at Time and Time 2 were significant between participants with COVID-19 and participants who did not have COVID-19 (B= -0.12 (0.04), 95% CI: -0.19, -0.04, p = 0.004), students compared to faculty and staff (B=-0.22 (0.05), -0.32, -0.12, p < 0.0001), between Republicans and Democrats (B-= -0.16 (0.07), 95% CI: -0.28, -0.03, p = 0.020, and between Independents and Democrats (B=-0.08 (0.04), 95% CI: -0.16, -0.002, p = 0.04). CONCLUSION: Race and ethnicity, political affiliation, and division may affect attitudes and behaviors in mask wearing. Further investigation into how characteristics influence public health measures such as mask wearing is needed to contain the spread of the COVID-19 virus, other infectious diseases, and future pandemics.

Assessment of the Implementation of the International Health Regulations during the COVID-19 Pandemic: Portugal as a Case Study.

INTRODUCTION: The International Health Regulations (IHR) were developed to prepare countries to deal with public health emergencies. The spread of SARS-CoV-2 underlined the need for international coordination, although few attempts were made to evaluate the integrated implementation of the IHR's core capacities in response to the COVID-19 pandemic. The aim of this study was to evaluate whether IHR shortcomings stem from non-compliance or regulatory issues, using Portugal as a European case study due to its size, organization, and previous discrepancies between self-reporting and peer assessment of the IHR's core capacities. METHODS: Fifteen public health medical residents involved in contact tracing in mainland Portugal interpreted the effectiveness of the IHR's core capabilities by reviewing the publicly available evidence and reflecting on their own field experience, then grading each core capability according to the IHR Monitoring Framework. The assessment of IHR enforcement considered efforts made before and after the onset of the pandemic, covering the period up to July 2021. RESULTS: Four out of nine core IHR capacities (surveillance; response; risk communication; and human resource capacity) were classified as level 1, the lowest. Only two were graded level 3 (preparedness; and laboratory), the highest. The remaining three) (national legislation, policy & financing; coordination and national focal point communication; and points of entry) were classified as level 2. CONCLUSION: Portugal exemplifies the extent to which implementation of the IHR was not fully achieved, which has resulted in the underperformance of several core capacities. There is a need to improve preparedness and international cooperation in order to harmonize and strengthen the global response to public health emergencies, with better political, institutional, and financial support.

Caminando hacia el final de la pandemia COVID-19: caso México / Moving towards the end of the COVID-19 pandemic: the case of Mexico

Introducción: se vive una crisis de confianza en la ciencia y una época de menosprecio a los conocimientos y evidencias. Las opiniones de los líderes políticos y otras figuras públicas ajenas a los problemas de salud tienen una mayor consideración y peso que los juicios emitidos por los expertos. Una evidencia que demuestra la debilidad de México en el campo de la salud son dos hechos en los cuales las autoridades del país son los culpables que son: la desaparición del Seguro Popular y la pobre respuesta a la pandemia de COVID-19. Conclusiones: la pandemia no termina por decreto, se logrará con cuidados y prevención realizada por el gobierno, instituciones y personal de salud y la sociedad (AU)

Introduction: we are living through a crisis of confidence in science and an era of disregard for knowledge and evidence. The opinions of political leaders and other public figures who are not involved in health problems are given greater consideration and weight than the judgments made by experts. Evidence that demonstrates Mexico's weakness in the field of health are two facts in which the country's authorities are to blame: the disappearance of Seguro Popular and the poor response to the COVID-19 pandemic. Conclusions: the pandemic does not end by decree, it will be achieved with care and prevention carried out by the government, health institutions and personnel and society (AU)

Compliance with recommended preventive behaviours and restrictions for Covid-19: an exploratory analysis of Italians' attitudes.

BACKGROUND AND AIM: as a reaction to the COVID-19 pandemic, countries all over the world have undertaken wide-scale measures to prevent and limit the spread of the virus. Suggested preventative measures mainly included "lockdown", social distancing, wearing facemasks, and vaccinations. The success of these measures was widely dependent on the cooperation of citizens. However, people reacted differently to the several types of restrictions and recommendations. Even if the majority followed the rules, others ignored them. This study aims to investigate the reasons for the compliance or violation of the rules developed to fight against the COVID-19 pandemic in Italy. METHODS: to answer the research question, the analysis of two different surveys conducted on a representative sample of Italians (N=2000) were conducted and analysed through descriptive statistics. RESULTS: the data collection agreed with published literature. Compliance with rules during emergencies followed diligence and altruistic patterns. Fear of sanctions did not seem to work in relation to rules compliance during emergency situations. The lack of clarity of regulations in terms of complexity or constant changes led to non-compliance even intervening as a neutralization technique. CONCLUSIONS: government's fear-based interventions did not seem to work since Italians tended to adhere to the rules primarily out of respect for legitimate authority. Future research should focus more on the topic of trust in institutions in emergency situations with the aim of highlighting the key points for successful governance, also in terms of rules compliance.

A weapon to fight against pervasive Omicron: systematic actions transiting to pre-COVID normal.

The Coronavirus Disease-2019 (COVID-19) pandemic is not just a health crisis but also a social crisis. Confronted with the resurgence of variants with massive infections, the triggered activities from personal needs may promote the spread, which should be considered in risk management. Meanwhile, it is important to ensure that the policy responses on citizen life to a lower level. In the face of Omicron mutations, we need to sum up the control experience accumulated, adapting strategies in the dynamic coevolution process while balancing life resumption and pandemic control, to meet challenges of future crises. We collected 46 cases occurring between 2021 and 2022, mainly from China, but also including five relevant cases from other countries around the world. Based on case studies, we combine micro-view individual needs/behaviors with macro-view management measures linking Maslow's hierarchy of needs with the transmission chain of Omicron clusters. The proposed loophole chain could help identify both individual and management loopholes in the spread of the virus. The systematic actions that were taken have effectively combated these ubiquitous vulnerabilities at lower costs and lesser time. In the dynamic coevolution process, the Chinese government has made effective and more socially acceptable prevention policies while meeting the divergent needs of the entire society at the minimum costs. Systematic actions do help maintain the balance between individuals' satisfaction and pandemic containment. This implies that risk management policies should reasonably consider individual needs and improve the cooperation of various stakeholders with targeted flexible measures, securing both public health and life resumption.

Impact of COVID-19 lockdowns on house sparrows: Comparative study from an Indian context.

Due to the outbreak of COVID-19, the last couple of years have been drastic in terms of human behavioural patterns. The pandemic has taught us key lessons about crisis, communication and misinformation. People were forced to stay at home for a very long duration because of the strict lockdown measures imposed by governments all over the globe. India was no exception, wherein the Indian government imposed several very strict lockdowns all across the country, which restricted human activities and their social behaviours. However, such restrictions were seen to have a positive impact on environment and ecology. In this paper, we aim to study the changes in House sparrow sightings, as a result of the lockdowns. It is postulated that the lockdowns give rise to increased House sparrow numbers, which we try to argue, using appropriate exploratory analysis and statistical modelling. We apply a specific "zero-inflated Poisson" regression model in this regard.

The impact of non-pharmaceutical interventions on the first COVID-19 epidemic wave in South Africa.

OBJECTIVE: In this study, we investigated the impact of COVID-19 NPIs in South Africa to understand their effectiveness in the reduction of transmission of COVID-19 in the South African population. This study also investigated the COVID-19 testing, reporting, hospitalised cases, excess deaths and COVID-19 modelling in the first wave of the COVID-19 epidemic in South Africa. METHODS: A semi-reactive stochastic COVID-19 model, the ARI COVID-19 SEIR model, was used to investigate the impact of NPIs in South Africa to understand their effectiveness in the reduction of COVID-19 transmission in the South African population. COVID-19 testing, reporting, hospitalised cases and excess deaths in the first COVID-19 epidemic wave in South Africa were investigated using regressional analysis and descriptive statistics. FINDINGS: The general trend in population movement in South African locations shows that the COVID-19 NPIs (National Lockdown Alert Levels 5,4,3,2) were approximately 30% more effective in reducing population movement concerning each increase by 1 Alert Level. The translated reduction in the effective SARS-CoV-2 daily contact number (ß) was 6.12% to 36.1% concerning increasing Alert Levels. Due to the implemented NPIs, the effective SARS-CoV-2 daily contact number in the first COVID-19 epidemic wave in South Africa was reduced by 58.1-71.1% while the peak was delayed by 84 days. The estimated COVID-19 reproductive number was between 1.98 to 0.40. During South Africa's first COVID-19 epidemic wave, the mean COVID-19 admission status in South African hospitals was 58.5%, 95% CI [58.1-59.0] in the general ward, 13.4%, 95% CI [13.1-13.7] in the intensive care unit, 13.3%, 95% CI [12.6-14.0] on oxygen, 6.37%, 95% CI [6.23-6.51] in high care, 6.29%, 95% CI [6.02-6.55] on ventilator and 2.13%, 95% CI [1.87-2.43] in isolation ward respectively. The estimated mean South African COVID-19 patient discharge rate was 11.9 days per patient. While the estimated mean of the South African COVID-19 patient case fatality rate (CFR) in hospital and outside the hospital was 2.06%, 95% CI [1.86-2.25] (deaths per admitted patients) and 2.30%, 95% CI [1.12-3.83](deaths per severe and critical cases) respectively. The relatively high coefficient of variance in COVID-19 model outputs observed in this study shows the uncertainty in the accuracy of the reviewed COVID-19 models in predicting the severity of COVID-19. However, the reviewed COVID-19 models were accurate in predicting the progression of the first COVID-19 epidemic wave in South Africa. CONCLUSION: The results from this study show that the COVID-19 NPI policies implemented by the Government of South Africa played a significant role in the reduction of COVID-19 active, hospitalised cases and deaths in South Africa's first COVID-19 epidemic wave. The results also show the use of COVID-19 modelling to understand the COVID-19 pandemic and the impact of regressor variables in an epidemic.

School closures significantly reduced arrests of black and latinx urban youth.

BACKGROUND & METHODS: Youth of color are surveilled and arrested by police at higher rates than their White peers, contributing to racial inequities across the life course and in population health. Previous research points to schools as an increasingly relevant site for youth criminalization, but existing studies emphasize within-school mechanisms, with limited analysis of policing in surrounding school areas. To fill this gap, we study changes in police arrests of youth after initial COVID-19 school closures in 2020 across four US cities overall and in relation to public school locations. We analyze geocoded arrest records and use interrupted time series negative binomial regression models with city and month fixed effects to estimate change in weekly arrest rates among White, Black, and Latinx youth. We estimate arrest densities within school areas before and after school closures using spatial buffers of 300 feet. RESULTS: In the immediate weeks and months following COVID-19 pandemic school closures, youth arrest rates fell dramatically and with lasting impacts compared to other age groups. During the period of remote learning, weekly youth arrest rates declined by 54.0% compared to youth arrests rates in 2019, adjusting for city and seasonality (Incident Rate Ratio 0.46, 95% CI: 0.41, 0.52). We estimate Black youth weekly arrests fell from 43.6 to 16.8 per 100,000, vs. 4.6 to 2.2 per 100,000 among White youth. However, Black youth arrest rates during the remote learning period were still nearly 5 times that of White youth pre-pandemic. We also find that youth arrest rates declined during two school closure periods: at the start of the pandemic in 2020 and during Summer 2019. A spatial analysis shows Black and Latinx youth arrest densities in the surrounding 300 feet of K-12 schools were at least 15 and 8.5 times that of White youth, respectively, in both pre- and remote-learning periods. CONCLUSIONS: Black and Latinx youth face a higher likelihood of being arrested near a school than do White youth and older age groups, and racial inequities in arrests remains after school closures. Our findings show school closures significantly reduced arrests of urban youth of color, and policies addressing youth criminalization and structural racism should consider the joint spatial context of schools and policing. Although school closures may have resulted in learning loss and harms to youth wellbeing, closures interrupted comparatively high levels of arrest for Black and Latinx youth.

Fogging to combat dengue: factors influencing stakeholders' attitudes in Malaysia.

BACKGROUND: Fogging is a conventional technique used to combat Aedes mosquitoes and prevent dengue disease. It is often implemented in outbreak areas or areas harbouring a high density of Aedes mosquitoes. Currently, studies on stakeholders' attitudes towards fogging are still limited in number. Therefore, this study aims to assess Malaysian attitudes, and identify the predicting factors influencing such attitudes. METHODS: A validated instrument was used to interview 399 randomly selected respondents from the public (n = 202, 50.6%) and scientists (n = 197, 49.4%) in the Klang Valley region of Malaysia. The data were analysed using PLS-SEM involving Smart-PLS software. RESULTS: The results confirmed that stakeholder attitudes toward fogging should be viewed in terms of a multi-dimensional association. The stakeholders surveyed were highly positive with regard to the application of fogging to control dengue but professed moderate concerns as to associated risks. The PLS-SEM analyses demonstrated that the perceived benefit was the most important factor influencing attitudes, followed by trust in key players. CONCLUSIONS: This result provides a good insight from the perspective of education and unravels the underlying fundamentals of stakeholders' attitudes toward the fogging technique. The findings also provide a positive indicator to the responsible parties involved to continue the usage of this technique in conjunction with improvements with regard to its safety aspects, and possibly in combination with other environmental-friendly alternatives in order to achieve a healthy environment without dengue in Malaysia.