COVID-19 Case Rates Research Articles

Municipal Ethnic Composition and Disparities in COVID-19 Infections in New Jersey: A Blinder-Oaxaca Decomposition Analysis.

COVID-19 has disproportionally impacted Latinx and Black communities in the US. Our study aimed to extend the understanding of ethnic disparities in COVID-19 case rates by using a unique dataset of municipal case rates across New Jersey (NJ) during the first 17 months of the pandemic. We examined the extent to which there were municipal-level ethnic disparities in COVID-19 infection rates during three distinct spikes in case rates over this period. Furthermore, we used the Blinder-Oaxaca decomposition analysis to identify municipal-level exposure and vulnerability factors that contributed to ethnic disparities and how the contributions of these factors changed across the three initial waves of infection. Two clear results emerged. First, in NJ, the COVID-19 infection risk disproportionally affected Latinx communities across all three waves during the first 17 months of the pandemic. Second, the exposure and vulnerability factors that most strongly contributed to higher rates of infection in Latinx and Black communities changed over time as the virus, alongside medical and societal responses to it, also changed. These findings suggest that understanding and addressing ethnicity-based COVID-19 disparities will require sustained attention to the systemic and structural factors that disproportionately place historically marginalized ethnic communities at greater risk of contracting COVID-19.

Online Conspiracy Groups: Micro-Bloggers, Bots, and Coronavirus Conspiracy Talk on Twitter

Conspiracies are consequential and social, yet online conspiracy groups that consist of individuals (and bots) seeking to explain events or a system have been neglected in sociology. We extract conspiracy talk about the COVID-19 pandemic on Twitter and use the biterm topic model (BTM) to provide a descriptive baseline for the discursive and social structure of online conspiracy groups. We find that individuals enter these communities through a gateway conspiracy theory before proceeding to extreme theories, and humans adopt more diverse conspiracy theories than do bots. Event-history analyses show that individuals tweet new conspiracy theories, and tweet inconsistent theories simultaneously, when they face a threat posed by a rising COVID-19 case rate and receive attention from others via retweets. By contrast, bots are less responsive to rising case rates, but they are more consistent, as they mainly tweet about how COVID-19 was deliberately created by sinister agents. These findings suggest human beings are bricoleurs who use conspiracy theories to make sense of COVID-19, whereas bots are designed to create moral panic. Our findings suggest that conspiracy talk by individuals is defensive in nature, whereas bots engage in offense.

Adherence of those at low risk of disease to public health measures during the COVID-19 pandemic: A qualitative study.

Public health measures (PHMs) proactively and reactively reduce the spread of disease. While these measures target individual behaviour, they require broad adherence to be effective. Consequently, the World Health Organization issued a special appeal to young adults, a known non-adherent population, for increased adherence with COVID-19 guidelines. However, little is known about why these low-risk individuals do or do not adhere to PHMs. This study investigates why young adults in a low-risk setting adhered to PHMs implemented during the COVID-19 pandemic. A qualitative research approach was chosen to gain an in-depth understanding of participants’ thoughts and experiences related to PHM adherence. Semi-structured interviews were conducted in April-May 2021 with 30 young adults living in Prince Edward Island (PEI), the province with the lowest COVID-19 case rate in Canada at that time. Thematic analysis was used to create a codebook based on the Theoretical Domains Framework, which was then inductively modified. The analysis identified eight themes that explained the adherence of young adults: (1) clear, purpose-driven adherence rationale, (2) developing trust in the local leadership, (3) adapting to novel measures, (4) manageable disruption, (5) adhering to reduce anxiety, (6) collective duty towards one’s community, (7) moral culpability and (8) using caution rather than compliance. Together, these themes demonstrate that young adults adhered to PHMs because of their sense of connection to their community, public health leadership, and concerns over stigma. We further argue that clear guidelines and communication from public health officials during both periods of high and low COVID-19 cases facilitate adherence. These findings are important for mitigating future public health emergencies as they explain why young adults, an important segment of the population whose adherence is critical to the success of PHMs, follow PHMs. Further, these findings can inform public health officials and other stakeholders aiming to develop successful adherence strategies.

Locality based Approach for containment of COVID-19 Infections in Pakistan’s High risk Districts-ICT

Abstract Background In May 2020, considering gradual restoration of all economical activities the Government of Pakistan updated containment strategy from locking down the whole country to locking down high-risk areas to mitigate COVID-19 spread. All districts having ≥300 cases/100,000 population. COVID-19 case incidence and test positivity rates by real-time RT-PCR before and after zonal lockdown were compared to assess whether the locality-based lockdowns can be used as an alternative to country lockdown to contain COVID-19 spread. Methods Smart lockdowns were implemented in ten localities in the Islamabad Capital Territory (ICT), having a population of 60,000 from 12 May 2020 to June 3, 2020. Movements were restricted. Entry and exit points were guarded by police. Any person with symptoms of fever, cough, or sore throat tested by real-time RT-PCR methods and reported within 24 hours of collection. To compare the rate of active cases and positivity rate by weeks, we performed a z-test for two proportions and set p < 0.05 as the level of significance. Results The red zone had 60,000 persons in 2.00 square kilometers. The rate of active COVID-19 cases significantly decreased (p < 0.0001) during intervention from 300/100,000 population pre-containment time to 22/100,000 population after the first three weeks of lockdown. The COVID-19 positivity rate also decreased significantly (p < 0.0001) from 24% (24/78) pre-containment to 5.3% during containment. A total of 3800 people were tested in the following three weeks of intervention and 26 cases were detected. Conclusions The smart lockdowns approach reduced COVID-19 transmission in the ICT district. This type of intervention was recommended to reduce the COVID-19 infection spread Key messages • Reduced COVID-19 transmission in the ICT district. • Keeping balance between life and economy.

COVID-19 epidemiology and changes in health service utilization in Uganda’s refugee settlements during the first year of the pandemic

BackgroundThe COVID-19 pandemic has been characterized by multiple waves with varying rates of transmission affecting countries at different times and magnitudes. Forced displacement settings were considered particularly at risk due to pre-existing vulnerabilities. Yet, the effects of COVID-19 in refugee settings are not well understood. In this study, we report on the epidemiology of COVID-19 cases in Uganda’s refugee settlement regions of West Nile, Center and South, and evaluate how health service utilization changed during the first year of the pandemic.MethodsWe calculate descriptive statistics, testing rates, and incidence rates of COVID-19 cases in UNHCR’s line list and adjusted odds ratios for selected outcomes. We evaluate the changes in health services using monthly routine data from UNHCR’s health information system (January 2017 to March 2021) and apply interrupted time series analysis with a generalized additive model and negative binomial distribution, accounting for long-term trends and seasonality, reporting results as incidence rate ratios.FindingsThe first COVID-19 case was registered in Uganda on March 20, 2020, and among refugees two months later on May 22, 2020 in Adjumani settlement. Incidence rates were higher at national level for the general population compared to refugees by region and overall. Testing capacity in the settlements was lower compared to the national level. Characteristics of COVID-19 cases among refugees in Uganda seem to align with the global epidemiology of COVID-19. Only hospitalization rate was higher than globally reported. The indirect effects of COVID-19 on routine health services and outcomes appear quite consistent across regions. Maternal and child routine and preventative health services seem to have been less affected by COVID-19 than consultations for acute conditions. All regions reported a decrease in consultations for respiratory tract infections.InterpretationCOVID-19 transmission seemed lower in settlement regions than the national average, but so was testing capacity. Disruptions to health services were limited, and mainly affected consultations for acute conditions. This study, focusing on the first year of the pandemic, warrants follow-up research to investigate how susceptibility evolved over time, and how and whether health services could be maintained.

Examining the effects of COVID-19 on pharmacy dispensing of naloxone and syringes sales across Massachusetts and New Hampshire

BackgroundCoronavirus disease 2019 (COVID-19) lockdowns disrupted access to harm reduction supplies and services known to be effective in overdose prevention and contributed to a worsening of the opioid crisis. However, because pharmacies can provide naloxone and sell over-the-counter (OTC) sterile syringes, their continued operation throughout the pandemic potentially reinforced a public health role as a distribution hub for safer use supplies. ObjectivesThe objective of this analysis was to examine patterns of naloxone and OTC syringe sale volume at 463 community pharmacies in 2 states with high overdose rates during the COVID-19 pandemic. MethodsWe analyzed weekly pharmacy-level dispensing data from January 5, 2020, to December 31, 2020, from one corporate community pharmacy chain in Massachusetts (n = 415 pharmacies) and New Hampshire (n = 48 pharmacies). Descriptive statistics and visualizations over the analytical period were generated as initial explorations of the outcome. Zero-inflated Poisson and negative binomial models were used to analyze distribution data along with county-level COVID-19 case rates and store-level COVID-19 testing location status during the same time. Interactions tested the effect of COVID-19 case rates on naloxone and OTC syringe sales. ResultsPharmacies that reported selling nonprescription syringes and dispensing naloxone during the study period averaged 210.13 OTC syringes sold and 0.53 naloxone prescriptions per week. Pharmacies in communities that experienced greater COVID-19 case burden also exhibited higher naloxone dispensing and OTC syringe sales during this period. The odds of selling OTC syringes increased over time but naloxone dispensing remained constant over the pandemic year. Pharmacies hosting COVID-19 testing tended to have lower OTC syringe sales and naloxone provision than nontesting sites. ConclusionDuring the COVID-19 pandemic, pharmacies provided harm reduction services and dispensed lifesaving medications by quickly adapting to fulfill community needs without disrupting co-located services for COVID-19 response.

Using Geocoding to Identify COVID-19 Outbreaks in Congregate Residential Settings: San Francisco's Outbreak Response in Single-Room Occupancy Hotels.

More than 500 single-room occupancy hotels (SROs), a type of low-cost congregate housing with shared bathrooms and kitchens, are available in San Francisco. SRO residents include essential workers, people with disabilities, and multigenerational immigrant families. In March 2020, with increasing concerns about the potential for rapid transmission of COVID-19 among a population with disproportionate rates of comorbidity, poor access to care, and inability to self-isolate, the San Francisco Department of Public Health formed an SRO outbreak response team to identify and contain COVID-19 clusters in this congregate residential setting. Using address-matching geocoding, the team conducted active surveillance to identify new cases and outbreaks of COVID-19 at SROs. An outbreak was defined as 3 separate households in the SRO with a positive test result for COVID-19. From March 2020 through February 2021, the SRO outbreak response team conducted on-site mass testing of all residents at 52 SROs with outbreaks identified through geocoding. The rate of positive COVID-19 tests was significantly higher at SROs with outbreaks than at SROs without outbreaks (12.7% vs 6.4%; P < .001). From March through May 2020, the rate of COVID-19 cases among SRO residents was higher than among residents of other settings (ie, non–SRO residents), before decreasing and remaining at an equal level to non–SRO residents during later periods of 2020. The annual case fatality rate for SRO residents and non–SRO residents was similar (1.8% vs 1.5%). This approach identified outbreaks in a setting at high risk of COVID-19 and facilitated rapid deployment of resources. The geocoding surveillance approach could be used for other diseases and in any setting for which a list of addresses is available.

Effects of the Government Response and Community Mobility on the COVID-19 Pandemic in Southeast Asia.

Preventive policies and mobility restrictions are believed to work for inhibiting the growth rate of COVID-19 cases; however, their effects have rarely been assessed and quantified in Southeast Asia. We aimed to examine the effects of the government responses and community mobility on the COVID-19 pandemic in Southeast Asian countries. The study extracted data from Coronavirus Government Response Tracker, COVID-19 Community Mobility Report, and Our World in Data between 1 March and 31 December 2020. The government responses were measured by containment, health, and economic support index. The community mobility took data on movement trends at six locations. Partial least square structural equation modeling was used for bi-monthly analyses in each country. Results show that the community mobility generally followed government responses, especially the containment index. The path coefficients of government responses to community mobility ranged from −0.785 to −0.976 in March to April and −0.670 to −0.932 in May to June. The path coefficients of community mobility to the COVID-19 cases ranged from −0.058 to −0.937 in March to April and from −0.059 to −0.640 in September to October. It suggests that the first few months since the mobility restriction implemented is the optimal time to control the pandemic.

Structured reflection increases intentions to reduce other people's health risks during COVID-19.

People believe they should consider how their behavior might negatively impact other people, Yet their behavior often increases others' health risks. This creates challenges for managing public health crises like the COVID-19 pandemic. We examined a procedure wherein people reflect on their personal criteria regarding how their behavior impacts others' health risks. We expected structured reflection to increase people's intentions and decisions to reduce others' health risks. Structured reflection increases attention to others' health risks and the correspondence between people's personal criteria and behavioral intentions. In four experiments during COVID-19, people (N=12,995) reported their personal criteria about how much specific attributes, including the impact on others' health risks, should influence their behavior. Compared with control conditions, people who engaged in structured reflection reported greater intentions to reduce business capacity (experiment 1) and avoid large social gatherings (experiments 2 and 3). They also donated more to provide vaccines to refugees (experiment 4). These effects emerged across seven countries that varied in collectivism and COVID-19 case rates (experiments 1 and 2). Structured reflection was distinct from instructions to carefully deliberate (experiment 3). Structured reflection increased the correlation between personal criteria and behavioral intentions (experiments 1 and 3). And structured reflection increased donations more among people who scored lower in cognitive reflection compared with those who scored higher in cognitive reflection (experiment 4). These findings suggest that structured reflection can effectively increase behaviors to reduce public health risks.

Analysis of Provincial Poverty in Indonesia (Case Study: Before the Covid 19 Pandemic and During the Covid 19 Pandemic)

Poverty uses three measurements, namely: the percentage of poor people (P0), the depth index (P1) and the severity index (P2). Poverty in 2018-2019 has decreased where the Covid 19 Pandemic has not yet occurred in Indonesia. After the Covid-19 Pandemic (2020-2021) there was a restriction on population mobility, thereby reducing income and having an impact on poverty. The object of research uses all provinces in Indonesia. Poverty data is sourced from the Central Statistics Agency and the Covid 19 Task Force. The purpose of the study is to compare poverty and the COVID-19 pandemic in every province in Indonesia. This study uses descriptive statistical analysis using data from 2019 and 2020. The results found five provinces with a high rate of COVID-19 cases including: West Java, Central Java, East Java, North Sumatra, and DI. Yogyakarta. The five provinces with the highest COVID-19 cases experienced an increase in poverty during the 2020 COVID-19 pandemic

Antibody Responses and CNS Pathophysiology of Mucormycosis in Chronic SARS Cov-2 Infection: Current Therapies Against Mucormycosis.

The incidence rate of opportunistic secondary infections through invasive fungi has been observed to be 14.5% to 27% in the SARS CoV pandemic during the year 2003. However, the incidence of SARS CoV-2 is accompanied by a substantial rise in secondary opportunistic infections like mucormycosis (black fungus), mainly in the immunocompromised individuals and diabetic patients taking steroids. Substantial rates of COVID-19 cases with mucormycosis were reported in India and other parts of the world. Previous research reports delineated the ability of Mucorales to invade the various tissues like lungs, brain, and sinus through the GRP78, and subsequently, this infection could invoke crusting, edema, and necrosis of the brain parenchyma, ptosis, proptosis, and vision loss due to intraorbital and intracranial complications. Similarities of these pathophysiological complications with already existing diseases are causing clinicians to face several challenges in order to diagnose and treat this disease effectively at the early stage. This minireview depicts the mucormycosis-induced immune and pathophysiological alterations in COVID-19 patients comorbid with diabetes and immunosuppression and also reported the various clinical manifestations, the therapeutic modalities, and the failures of anti-fungal vaccines. Therefore, the emerging mucormycosis in COVID-19 patients needs rapid investigation and selective optimization of the effective therapeutic modalities, including antifungal vaccines, to minimize the mortality rate.

Tinder-Ly Yours: An Exploratory Study of Malaysian Indian Youths Online Dating Through The Culture

The pandemic has shifted the way we meet new people and thus, changed the concept of going on a date. With the sporadic and growing rates of Covid-19 cases, it may be difficult to find a relationship and maintain one while exercising social-distance. As we adjusted to this temporary reality, the dating sphere continued reinvent ways to connect people. “Today”, more Indian Malaysian youths have increased their presence on dating apps in search of love and intimacy despite their “traditional” Indian courtship practices. The main thrust of this study is to examine why the smartphone application ‘Tinder’ is increasingly popular among Malaysian Indian youth and to investigate why and how the youth use Tinder during this pandemic. The Uses and Gratifications Theory (U&amp;G) holds major assumptions that individuals are active, rational, and objective, to the extent of being almost goal-oriented in their choices. This study conducted 30 in-depth, semi-structured interviews via convenience and snowball sampling found that online dating behaviour has the potential to help scholars have deeper understanding of how the Tinder mobile application integrated with existing religions and cultures gives insights into the nature of technological change as well as adaptation in society. This is by providing new insights into existing interpersonal communication theories focusing on relationship formation. Keywords: Courtships, Cultural studies, Indian, Tinder, Youth.

The longitudinal effects of stress and fear on psychiatric symptoms in mothers during the COVID-19 pandemic.

The COVID-19 pandemic has been particularly difficult for mothers. Women with a history of peripartum depression (PPD) may be vulnerable to relapse. We sought to understand changes in depressive and anxious symptoms throughout the pandemic and which stressors increased symptoms in women with a history of PPD. In June 2020, all US participants with a history of PPD (n = 12,007) in the global MomGenes Fight PPD study were invited to the COVID-19 follow-up study. Respondents (n = 2163, 18%) were sent biweekly and then monthly surveys until January 31, 2022. We employed time-varying effects models to evaluate trajectories of depressive (patient health questionnaire, PHQ-9) and anxious (generalized anxiety disorder, GAD-7) symptoms and to estimate longitudinal associations between perceived stress, fears, COVID-19 case rates, and symptoms. Peaks of PHQ-9, GAD-7, PSS, and perceived COVID-19 risk scores corresponded with timing of national COVID-19 case surges. High perceived stress was the strongest predictor of PHQ-9 (beta = 7.27; P = 1.48e − 38) and GAD-7 (beta = 7.73; P = 6.19e − 70). Feeling lack of control and unlikely to survive increased PHQ-9 and GAD-7 scores by 2 points. COVID-19 case rates, pandemic restrictions, and region were not independently associated with symptoms. This study suggests that the collective trauma of the pandemic has significantly affected mothers with a history of PPD, exemplified by high levels of perceived stress and the strong association with depressive and anxious symptoms. The next pandemic phase is uncertain, but will continue to influence mental health collectively and dynamically. Interventions must be flexible and responsive and should address fear, trauma, and feelings of control, particularly for mothers with a history of PPD.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00737-022-01265-1.

Predictors of COVID-19 vaccination rate in USA: A machine learning approach

In this study, we examine state-level features and policies that are most important in achieving a threshold level vaccination rate to curve the effects of the COVID-19 pandemic. We employ CHAID, a decision tree algorithm, on three different model specifications to answer this question based on a dataset that includes all the states in the United States. Workplace travel emerges as the most important predictor; however, the governors’ political affiliation (PA) replaces it in a more conservative feature set that includes economic features and the growth rate of COVID-19 cases. We also employ several alternative algorithms as a robustness check. Results from these checks confirm our original findings regarding workplace travels and political affiliation. The accuracy under different model specifications ranges from 80%–88%, whereas the sensitivity is between 92.5%–100%. Our findings provide actionable policy insights to increase vaccination rates and combat the COVID-19 pandemic.

Public Interest and Accessibility of Telehealth in Japan: Retrospective Analysis Using Google Trends and National Surveillance.

BackgroundRecently, the use of telehealth for patient treatment under the COVID-19 pandemic has gained interest around the world. As a result, many infodemiology and infoveillance studies using web-based sources such as Google Trends were reported, focusing on the first wave of the COVID-19 pandemic. Although public interest in telehealth has increased in many countries during this time, the long-term interest has remained unknown among people living in Japan. Moreover, various mobile telehealth apps have become available for remote areas in the COVID-19 era, but the accessibility of these apps in epidemic versus nonepidemic regions is unknown.ObjectiveWe aimed to investigate the public interest in telehealth during the first pandemic wave and after the wave in the first part of this study, and the accessibility of medical institutions using telehealth in the epidemic and nonepidemic regions, in the second part.MethodsWe examined and compared the first wave and after the wave with regards to severe cases, number of deaths, relative search volume (RSV) of telehealth and COVID-19, and the correlation between RSV and COVID-19 cases, using open sources such as Google Trends and the Japanese Ministry of Health, Labour and Welfare (JMHLW) data. The weekly mean and the week-over-week change rates of RSV and COVID-19 cases were used to examine the correlation coefficients. In the second part, the prevalence of COVID-19 cases, severe cases, number of deaths, and the telehealth accessibility rate were compared between epidemic regions and nonepidemic regions, using the JMHLW data. We also examined the regional correlation between telehealth accessibility and the prevalence of COVID-19 cases.ResultsAmong the 83 weeks with 5 pandemic waves, the overall mean for the RSV of telehealth and COVID-19 was 11.3 (95% CI 8.0-14.6) and 30.7 (95% CI 27.2-34.2), respectively. The proportion of severe cases (26.54% vs 18.16%; P<.001), deaths (5.33% vs 0.99%; P<.001), RSV of telehealth (mean 33.1, 95% CI 16.2-50.0 vs mean 7.3, 95% CI 6.7-8.0; P<.001), and RSV of COVID-19 (mean 52.1, 95% CI 38.3-65.9 vs mean 26.3, 95% CI 24.4-29.2; P<.001) was significantly higher in the first wave compared to after the wave. In the correlation analysis, the public interest in telehealth was 0.899 in the first wave and –0.300 overall. In Japan, the accessibility of telehealth using mobile apps was significantly higher in epidemic regions compared to nonepidemic regions in both hospitals (3.8% vs 2.0%; P=.004) and general clinics (5.2% vs 3.1%; P<.001). In the regional correlation analysis, telehealth accessibility using mobile apps was 0.497 in hospitals and 0.629 in general clinics.ConclusionsAlthough there was no long-term correlation between the public interest in telehealth and COVID-19, there was a regional correlation between mobile telehealth app accessibility in Japan, especially for general clinics. We also revealed that epidemic regions had higher mobile telehealth app accessibility. Further studies about the actual use of telehealth and its effect after the COVID-19 pandemic are necessary.

Associations between local COVID-19 case rates, pandemic-related financial stress and parent and child functioning.

The COVID-19 global crisis led to unprecedented disruption of family routines and heightened family stress. This study examines the effects of local COVID-19 case rates and pandemic-related financial stress on family processes (e.g., caregiving behavior) and school-aged children's outcomes. The project was launched shortly after stay-at-home orders began in the U.S. Data were collected online using Amazon's Mechanical Turk (MTurk), which allowed for nationwide recruitment. Using four waves of data (N = 308), with initial data collected between 4/20/20 and 5/6/20 and 2-3 weeks between each wave, this study examined the influence of local rates of COVID-19 infection on pandemic-related financial stress and the association of these constructs on maternal psychological distress and negative parenting. We also examined the potential cascade linking COVID-19 case rates and pandemic-related financial stress with child behavior problems via maternal psychological distress and negative parenting behavior, while controlling for prior child behavior problems. In line with hypotheses, higher Wave 1 (W1) pandemic-related financial stress was significantly associated with higher Wave 2 (W2) maternal psychological distress, which was significantly associated with higher Wave 3 (W3) negative parenting, which, in turn, was significantly associated with higher Wave 4 (W4) child behavior problems. In addition, the indirect effect of W1 pandemic-related financial stress on W3 negative parenting through W2 maternal psychological distress was significant. Higher W1 local COVID-19 case rates were significantly related to higher W3 negative parenting. Results suggest local COVID-19 case rates and pandemic-related financial stressors are associated with poorer child and family functioning. Implications for policy and practice are discussed. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

What strategies have been effective in optimising COVID-19 vaccine uptake in Australia and internationally?

A key public health measure protecting the population from COVID-19 is vaccination. Unvaccinated people have higher COVID-19 case rates and death rates than those who are fully or partially vaccinated. It has, and continues to be, critical to optimise COVID-19 vaccination uptake in the community. The aim of this study was to identify population groups who were less likely tobe fully vaccinated against COVID-19 and strategies that were successful in increasing uptake in these often hard-to-reach groups. Strategies that have successfully increased COVID-19 vaccine uptake may also be effective in enhancing uptake across a range of vaccine-preventable diseases. These strategies include collaboration and building trust with local communities, targeted communication and education, optimising access to vaccines and the use of targeted incentives. Primary care providers are often central to these strategies and are well placed to take the time that people need to shift from uncertain to becoming vaccinated.

Gambaran Faktor Perilaku COVID-19 pada Mahasiswa di Universitas Cenderawasih Kota Jayapura Provinsi Papua

Background: The rate of COVID-19 cases is still high in Jayapura City to date in one day it can contribute 30 to 35 positive patients. The form of prevention behavior in students has not been optimally implemented. the addition of positive cases every day can be triggered due to the lack of information related to the corona virus. The purpose of this study was to describe the behavioral factors to prevent COVID-19 in students.Methods: The population in this study were students of Cenderawasih University, Jayapura City. The study was conducted in January – February 2021 on 100 subjects selected by purposive sampling technique. Subjects were measured using an online questionnaire containing questions and statements regarding research variables such as knowledge, attitudes, practices, sources of information, social support and support from health workers. Data were analyzed by univariate analysis and bivariate analysis.Result: The results showed that 67% of students' level of knowledge about the causes, symptoms, modes of transmission and forms of prevention of COVID-19 was good, 58% of students' attitudes were quite good in seeking information and understanding forms of the spread of COVID-19 and 53% of students' practice levels in prevention. COVID-19 is good, with 49% of students getting information through social media, 100% of students getting social support, and 45% getting support from health workers.Conclusion : Students have received social support and support from health workers in preventing COVID-19. the majority of students have good knowledge but there are still students with less than optimal attitudes and practices.

Impact of Temperature and Population Size on the Spread of COVID-19 in Nigeria: A Robust Regression Approach

Background: COVID-19, a global pandemic ravaging many countries, shares some semblances with influenza, whose transmission can be affected by many factors. Atmospheric temperature and population density have been identified as two key factors influencing the spread of viruses. Nigerian states with different weather patterns and varying populations across her states have recorded about 173,908 COVID-19 cumulative confirmed cases between March 2020 and July 2021. Methods: Data sets of confirmed Covid-19 cases, average monthly temperature and population of each State, and Nigeria’s Federal Capital Territory were obtained. A test of assumptions of linear regression was carried out and there is the presence of outliers in the dataset. M-estimator as an alternative to Ordinary Least Square (O.L.S.) estimator for regression analysis was used to investigate the impacts of each State’s population size and atmospheric temperature on the rate of COVID-19 cases confirmed. The spearman rank correlation coefficient was also used to investigate the strength of the relationship be-tween the confirmed cases, the population and temperature. Results: Results show no multicollinearity (VIF=1.041) between the independent variables, and there is no autocorrelation as the Durbin-Watson test value gives 2.113 (approximately 2). There is a weak positive correlation between cumulative confirmed cases and population (r = 0.281), but a weak negative correlation exists between COVID-19 cumulative confirmed cases and atmospheric temperature (r = -0.341). For OLS estimation method, only population is significant (β1= 0.002, p &lt; 0.002) but the population (β1= 0.0006, p &lt; 0.05) and the atmospheric temperature ( β2= -683, p &lt; 0.05) are both significant when M-estimation method was applied. Conclusion: The findings in this study show that population size and temperature are important factors in the spread of Covid-19. The spread of the pandemic may be partially suppressed with higher temperatures but increases with an increased population.

Empirical Study of Hate Speech in Social Media During COVID-19 Crisis in the United States

As the COVID-19 outbreak, hate speech on social media towards Chinese and other Asian groups has encouraged "Sinophobia". To capture the situation of hate speech on Twitter, we hydrated the tweets discussing COVID-19, written in English language and have location within the USA. These tweets hydrated from Twitter API in span of 5 months (153 days). We have obtained 543,943 tweets in which we identify 40,579 Hate Speech occurrences. We categorized and analyzed them according to Pysentimiento model which is based on BERT models and, Latent Dirichlet Allocation Model (LDA). The results indicate that there are substantial associations between the increased amount of hate speech and the increased rate of deaths due to COVID-19,increased rate of new COVID-19 cases, and negative tests rate.