Search

The presence of heterogeneity in susceptibility, differences between hosts in their likelihood of becoming infected, can fundamentally alter disease dynamics and public health responses, for example, by changing the final epidemic size, the duration of an epidemic, and even the vaccination threshold required to achieve herd immunity. Yet, heterogeneity in susceptibility is notoriously difficult to detect and measure, especially early in an epidemic. Here we develop a method that can be used to detect and estimate heterogeneity in susceptibility given contact by using contact tracing data, which is typically collected early in the course of an outbreak. This approach provides the capability, given sufficient data, to estimate and account for the effects of this heterogeneity before they become apparent during an epidemic. It additionally provides the capability to analyze the wealth of contact tracing data available for previous epidemics and estimate heterogeneity in susceptibility for disease systems in which it has never been estimated previously. The premise of our approach is that highly susceptible individuals become infected more often than less susceptible individuals, and so individuals not infected after appearing in contact networks should be less susceptible than average. This change in susceptibility can be detected and quantified when individuals show up in a second contact network after not being infected in the first. To develop our method, we simulated contact tracing data from artificial populations with known levels of heterogeneity in susceptibility according to underlying discrete or continuous distributions of susceptibilities. We analyzed this data to determine the parameter space under which we are able to detect heterogeneity and the accuracy with which we are able to estimate it. We found that our power to detect heterogeneity increases with larger sample sizes, greater heterogeneity, and intermediate fractions of contacts becoming infected in the discrete case or greater fractions of contacts becoming infected in the continuous case. We also found that we are able to reliably estimate heterogeneity and disease dynamics. Ultimately, this means that contact tracing data alone is sufficient to detect and quantify heterogeneity in susceptibility. Author summary: Hosts often vary in their likelihood of contracting an infectious disease. This variation is referred to as heterogeneity in susceptibility, and it can have major public health consequences. However, heterogeneity in susceptibility is notoriously difficult to detect and quantify, and so, it has often been left out of mathematical models and ignored by decision makers. Here, we present a novel method that can be used to detect and quantify heterogeneity in susceptibility using only contact tracing data. The premise is that if heterogeneity is present, the average individual that did not become infected after appearing in a contact network would have lower susceptibility to infection than the average individual that has never appeared in a contact network. By measuring the difference in susceptibility between these two groups of individuals, which we assess with contact tracing data, it is possible to detect and quantify the level of heterogeneity. We demonstrate the application of this method and explore the method's power and accuracy using simulated contact tracing data. [ABSTRACT FROM AUTHOR]

We evaluate approaches to vaccine distribution using an agent-based model of human activity and COVID-19 transmission calibrated to detailed trends in cases, hospitalizations, deaths, seroprevalence, and vaccine breakthrough infections in Florida, USA. We compare the incremental effectiveness for four different distribution strategies at four different levels of vaccine supply, starting in late 2020 through early 2022. Our analysis indicates that the best strategy to reduce severe outcomes would be to actively target high disease-risk individuals. This was true in every scenario, although the advantage was greatest for the intermediate vaccine availability assumptions and relatively modest compared to a simple mass vaccination approach under high vaccine availability. Ring vaccination, while generally the most effective strategy for reducing infections, ultimately proved least effective at preventing deaths. We also consider using age group as a practical surrogate measure for actual disease-risk targeting; this approach also outperforms both simple mass distribution and ring vaccination. We find that quantitative effectiveness of a strategy depends on whether effectiveness is assessed after the alpha, delta, or omicron wave. However, these differences in absolute benefit for the strategies do not change the ranking of their performance at preventing severe outcomes across vaccine availability assumptions. Author Summary: We use our agent-based model of SARS-CoV-2 transmission to evaluate alternative vaccine distribution strategies over a range of vaccine supply scenarios. We find that strategies targeting transmission (e.g., ring vaccination) perform best in preventing infections, but targeting disease risk prevents more instances of severe outcomes. Specifically, strategies based on age, or age and comorbidities—which do not require contact tracing—resulted in the fewest hospitalizations in our model. These strategy rankings held true across all vaccine supply scenarios and were robust to the introduction of SARS-CoV-2 variants. While the quantitative results cannot be directly applied to other settings (as we used a synthetic population calibrated to the State of Florida), the rankings of strategies should be more generalizable. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic is the most significant worldwide health catastrophe, with massive impacts observed particularly among the healthcare workers. Stress among healthcare workers is a significant and pervasive issue that can have profound implications for both the well-being of healthcare professionals and the quality of patient care. This study aimed to determine the prevalence of stress related to the COVID-19 pandemic and the associated factors among the healthcare workers (HCWs). Methods: A retrospective cross-sectional study was conducted involving 533 HCWs in Kota Setar District Health Office. Related data was collected between January and June 2021. Stress was measured using the Depression Anxiety Depression Scale 21 (DASS-21). Other variables included in this study were sociodemographic and employment factors. The associated factors and predictors were determined by employing chi-square test and multivariate logistic models. Results: COVID-19 related stress was reported at 10.5%. HCWs who work at the district health offices and those with degree or higher qualifications had 2.3 (AOR = 2.310, 95% CI: 1.177–4.535) and 3 (AOR = 2.899, 95% CI: 1.613–5.211) higher odds of experiencing stress compared to those working in the clinics and had lower qualifications (diploma or less). Conclusions: The mental wellbeing of the HCWs participated in this study had been affected negatively by the COVID-19 pandemic, resulting in one in 10th of the HCWs were experiencing stress during the COVID-19 pandemic, with higher risk observed among those working at the district health office and HCWs with higher qualifications or ranking. This is expected since COVID-19 was a new and unprecedented outbreak associated with massive number of mortalities that requires active contact tracing and surveillance which commonly conducted at district health office level. Active intervention needed to cope with the overwhelming stress and working condition to ensure effective rehabilitation are in place and quality of work were not jeopardized. [ABSTRACT FROM AUTHOR]

Introduction: The traditional approach to epidemic control has been to slow down the rate of infection while building up healthcare capacity, resulting in a flattened epidemic curve. Advancements in bio-information-communication technology (BICT) have enabled the preemptive isolation of infected cases through efficient testing and contact tracing. This study aimed to conceptualize the BICT-enabled epidemic control (BICTEC) and to document its relationships with epidemic curve shaping and epidemic mitigation performance. Methods: Daily COVID-19 incidences were collected from outbreak to Aug. 12, 2020, for nine countries reporting the first outbreak on or before Feb. 1, 2020. Key epidemic curve determinants–peak height (PH), time to peak (TTP), and area under the curve (AUC)–were estimated for each country, and their relationships were analyzed to test if epidemic curves peak quickly at a shorter height. CFR (Case Fatality Rate) and CI (Cumulative Incidence) were compared across the countries to identify relationships between epidemic curve shapes and epidemic mitigation performance. Results: China and South Korea had the quickest TTPs (40.70 and 45.37 days since outbreak, respectively) and the shortest PHs (2.95 and 4.65 cases per day, respectively). Sweden, known for its laissez-faire approach, had the longest TTP (120.36) and the highest PH (279.74). Quicker TTPs were correlated with shorter PHs (ρ = 0·896, p = 0·0026) and lower AUCs (0.790, p = 0.0028), indicating that epidemic curves do not follow a flattened trajectory. During the study period, countries with quicker TTPs tended to have lower CIs (ρ =.855, P =.006) and CFRs (ρ = 0.684, P =.061). For example, South Korea, with the second-quickest TTP, reported the second lowest CI and the lowest CFR. Conclusions: Countries that experienced early COVID-19 outbreaks demonstrated the epidemic curves that quickly peak at a shorter height, indicating a departure from the traditional flattened trajectory. South Korea's BICTEC was found to be at least as effective as most lockdowns in reducing CI and CFR. [ABSTRACT FROM AUTHOR]

The COVID-19 outbreak led governmental officials to close many businesses and schools, including colleges and universities. Thus, the ability to resume normal campus operation required adoption of safety measures to monitor and respond to COVID-19. The objective of this study was to determine the efficacy of wastewater-based epidemiology as a surveillance method in monitoring COVID-19 on a college campus. The use of wastewater monitoring as part of a surveillance program to control COVID-19 outbreaks at East Carolina University was evaluated. During the Spring and Fall 2021 semesters, wastewater samples (N = 830) were collected every Monday, Wednesday, and Friday from the sewer pipes exiting the dormitories on campus. Samples were analyzed for SARS-CoV-2 and viral quantification was determined using qRT-PCR. During the Spring 2021 semester, there was a significant difference in SARS-CoV-2 virus copies in wastewater when comparing dorms with the highest number student cases of COVID-19 and those with the lowest number of student cases, (p = 0.002). Additionally, during the Fall 2021 semester it was observed that when weekly virus concentrations exceeded 20 copies per ml, there were new confirmed COVID-19 cases 85% of the time during the following week. Increases in wastewater viral concentration spurred COVID-19 swab testing for students residing in dormitories, aiding university officials in effectively applying COVID testing policies. This study showed wastewater-based epidemiology can be a cost-effective surveillance tool to guide other surveilling methods (e.g., contact tracing, nasal/salvia testing, etc.) to identify and isolate afflicted individuals to reduce the spread of pathogens and potential outbreaks within a community. [ABSTRACT FROM AUTHOR]

Background: Taiwan was a coronavirus disease 2019 (COVID-19) outlier, with an extraordinarily long transmission-free record: 253 days without locally transmitted infections while the rest of the world battled wave after wave of infection. The appearance of the alpha variant in May 2021, closely followed by the delta variant, disrupted this transmission-free streak. However, despite low vaccination coverage (<1%), outbreaks were well-controlled. Methods: This study analyzed the time to border closure and conducted one-sample t test to compare between Taiwan and Non-Taiwan countries prior to vaccine introduction. The study also collected case data to observe the dynamics of omicron transmission. Time-varying reproduction number,Rt, was calculated and was used to reflect infection impact at specified time points and model trends of future incidence. Results: The study analyzed and compare the time to border closure in Taiwan and non-Taiwan countries. The mean times to any border closure from the first domestic case within each country were -21 and 5.98 days, respectively (P <.0001). The Taiwanese government invested in quick and effective contact tracing with a precise quarantine strategy in lieu of a strict lockdown. Residents followed recommendations based on self-discipline and unity. The self-discipline in action is evidenced in Google mobility reports. The central and local governments worked together to enact non-pharmaceutical interventions (NPIs), including universal masking, social distancing, limited unnecessary gatherings, systematic contact tracing, and enhanced quarantine measures. The people cooperated actively with pandemic-prevention regulations, including vaccination and preventive NPIs. Conclusions: This article describes four key factors underlying Taiwan's success in controlling COVID-19 transmission: quick responses; effective control measures with new technologies and rolling knowledge updates; unity and cooperation among Taiwanese government agencies, private companies and organizations, and individual citizens; and Taiwanese self-discipline. [ABSTRACT FROM AUTHOR]

Isolating COVID-19 cases and quarantining their close contacts can prevent COVID-19 transmissions but also inflict harm. We analysed isolation and quarantine orders by the local public health agency in Berlin-Reinickendorf (Germany) and their dependence on the recommendations by the Robert Koch Institute, the national public health institute. Between 3 March 2020 and 18 December 2021 the local public health agency ordered 24 603 isolations (9.2 per 100 inhabitants) and 45 014 quarantines (17 per 100 inhabitants) in a population of 266 123. The mean contacts per case was 1.9. More days of quarantine per 100 inhabitants were ordered for children than for adults: 4.1 for children aged 0-6, 5.2 for children aged 7-17, 0.9 for adults aged 18-64 and 0.3 for senior citizens aged 65-110. The mean duration for isolation orders was 10.2 and for quarantine orders 8.2 days. We calculated a delay of 4 days between contact and quarantine order. 3484 contact persons were in quarantine when they developed an infection. This represents 8% of all individuals in quarantine and 14% of those in isolation. Our study quantifies isolation and quarantine orders, shows that children had been ordered to quarantine more than adults and that there were fewer school days lost to isolation or quarantine as compared to school closures. Our results indicate that the recommendations of the Robert Koch Institute had an influence on isolation and quarantine duration as well as contact identification and that the local public health agency was not able to provide rigorous contact tracing, as the mean number of contacts was lower than the mean number of contacts per person known from literature. Additionally, a considerable portion of the population underwent isolation or quarantine, with a notable number of cases emerging during the quarantine period. [ABSTRACT FROM AUTHOR]

Background: Contact tracing is a key component in controlling the spread of COVID-19, however little research has focused on learning from the experiences of contact tracing staff. Harnessing learning from those in this role can provide valuable insights into the process of contact tracing and how best to support staff in this crucial role. Methods: Thematic analysis was used to analyse 47 semi-structured interviews conducted with contact tracing staff via telephone or Zoom at three time points in 2021: March, May and September-October. Results: Six themes related to the contact tracing role were identified, including training, workforce culture, systems issues, motivation and support. While initially nervous in the role, participants were motivated to contribute to the pandemic response and believed the role provided them with valuable transferable skills. Participants described the training as having improved over time while desiring more proactive training. Sources of frustration included a perceived lack of opportunity for feedback and involvement in process changes, feelings of low autonomy, and a perception of high staff turnover. Participants expressed a need for improved communication of formal emotional supports. Increased managerial support and provision of opportunities for career advancement may contribute to increased motivation among staff. Conclusions: These findings identify the experiences of contact tracing staff working during the COVID-19 pandemic, and have important implications for the improvement of the contact tracing system. Recommendations based on learning from participants offer suggestions as to how best to support the needs of contact tracing staff during a pandemic response. [ABSTRACT FROM AUTHOR]

Introduction: Screening household contacts of TB patients and providing TB preventive therapy (TPT) is a key intervention to end the TB epidemic. Global and timely implementation of TPT in household contacts, however, is dismal. We adapted the 7-1-7 timeliness metric designed to evaluate and respond to infectious disease outbreaks or pandemics, and assessed the feasibility, enablers and challenges of implementing this metric for screening and management of household contacts of index patients with bacteriologically-confirmed pulmonary TB in Karachi city, Pakistan. Methods: We conducted an explanatory mixed methods study with a quantitative component (cohort design) followed by a qualitative component (descriptive design with focus group discussions). Results: From January-June 2023, 92% of 450 index patients had their household contacts line-listed within seven days of initiating anti-TB treatment ("first 7"). In 84% of 1342 household contacts, screening outcomes were ascertained within one day of line-listing ("next 1"). In 35% of 256 household contacts eligible for further evaluation by a medical officer (aged ≤5 years or with chest symptoms), anti-tuberculosis treatment, TPT or a decision for no drugs was made within seven days of symptom screening ("second 7"). The principal reason for not starting anti-tuberculosis treatment or TPT was failure to consult a medical officer: only 129(50%) of 256 contacts consulted a medical officer. Reasons for poor performance in the "second 7" component included travel costs to see a medical officer, loss of daily earnings and fear of a TB diagnosis. Field staff reported that timeliness metrics motivated them to take prompt action in household contact screening and TPT provision and they suggested these be included in national guidelines. Conclusions: Field staff found "7-1-7" timeliness metrics to be feasible and useful. Integration of these metrics into national guidelines could improve timeliness of diagnosis, treatment and prevention of TB within households of index patients. [ABSTRACT FROM AUTHOR]

People continue to use technology in new ways, and how governments harness digital information should consider privacy and security concerns. During COVID19, numerous countries deployed digital contact tracing that collect location data from user's smartphones. However, these apps had low adoption rates and faced opposition. We launched an interdisciplinary study to evaluate smartphone location data concerns among college students in the US. Using interviews and a large survey, we find that college students have higher concerns regarding privacy, and place greater trust in local government with their location data. We discuss policy recommendations for implementing improved contact tracing efforts. [ABSTRACT FROM AUTHOR]

The impact of the COVID-19 pandemic on University students has been a topic of fiery debate and of public health research. This study demonstrates the use of a combination of spatiotemporal epidemiological models to describe the trends in COVID-19 positive cases on spatial, temporal and spatiotemporal scales. In addition, this study proposes new epidemiological metrics to describe the connectivity between observed positivity; an analogous metric to the R number in conventional epidemiology. The proposed indices, Rspatial, Rspatiotemporal and Rscaling will aim to improve the characterisation of the spread of infectious disease beyond that of the COVID-19 framework and as a result inform relevant public health policy. Apart from demonstrating the application of the novel epidemiological indices, the key findings in this study are: firstly, there were some Intermediate Zones in Edinburgh with noticeably high levels of COVID-19 positivity, and that the first outbreak during the study period was observed in Dalry and Fountainbridge. Secondly, the estimation of the distance over which the COVID-19 counts at the halls of residence are spatially correlated (or related to each other) was found to be 0.19km (0.13km to 0.27km) and is denoted by the index, Rspatial. This estimate is useful for public health policy in this setting, especially with contact tracing. Thirdly, the study indicates that the association between the surrounding community level of COVID-19 positivity (Intermediate Zones in Edinburgh) and that of the University of Edinburgh's halls of residence was not statistically significant. Fourthly, this study reveals that relatively high levels of COVID-19 positivity were observed for halls for which higher COVID-19 fines were issued (Spearman's correlation coefficient = 0.34), and separately, for halls which were non-ensuite relatively to those which were not (Spearman's correlation coefficient = 0.16). Finally, Intermediate Zones with the highest positivity were associated with student residences that experienced relatively high COVID-19 positivity (Spearman's correlation coefficient = 0.27). [ABSTRACT FROM AUTHOR]

This cross-sectional study evaluated COVID-19 contact tracing efforts to identify variations in contact tracing outcomes in different population subgroups. Contact tracing was a critical tool to slow the COVID-19 epidemic. A literature gap evaluating contact tracing elicitation exits, particularly on prioritized groups. We analyzed data from COVID-19 cases linking statewide case management, immunization, laboratory testing, and hospitalization databases in New York State (NYS) outside of New York City from February 1 to November 30, 2021. Focus was cases in home-based residential settings (excluding congregate care) and prioritized groups (educational institutions, large households, close quarters, higher-risk persons, hospitalized). The primary outcome was completed interviews that provided a contact. Of the 550,850 cases interviewed during the study period, 316,645 (57.5%) provided at least one contact. Adults aged 18 to 49 years were most likely to provide contacts than those aged 65 years and older (adjusted odds ratio [aOR], 1.42; 95% confidence interval [CI], 1.39–1.45). Compared to unvaccinated cases, boosted individuals (aOR, 1.61; 95% CI, 1.50–1.73) were most likely to provide contacts, followed by persons with only a primary vaccine series (aOR, 1.3; 95%CI, 1.28–1.33) and partially vaccinated (aOR, 1.21; 95%CI, 1.18–1.24). Repeat cases (aOR, 1.07; 95%CI, 1.01–1.14), pregnant persons (aOR, 1.26; 95% CI, 1,19–1.34), those with underlying conditions (aOR 1.22; 95%CI, 1.20–1.23), and those in K-12 settings (aOR 1.55; 95%CI, 1.50–1.61) were more likely to provide contacts. There was no clear association between hospitalized, while zip code level income may (aOR, 1.006; 95%CI, 1.003, 1.009). Persons from larger households were more likely to provide contacts: aOR for two or more persons vs. one person households ranged from 2.49 to 4.7 (95%CI, 2.20–4.78). Our findings indicate success in eliciting contacts from prioritized groups and identify variable contact elicitation outcomes from different population groups. These results may serve as a tool for future contact tracing efforts. [ABSTRACT FROM AUTHOR]

Mathematical models have suggested that spatially-targeted screening interventions for tuberculosis may efficiently accelerate disease control, but empirical data supporting these findings are limited. Previous models demonstrating substantial impacts of these interventions have typically simulated large-scale screening efforts and have not attempted to capture the spatial distribution of tuberculosis in households and communities at a high resolution. Here, we calibrate an individual-based model to the locations of case notifications in one district of Lima, Peru. We estimate the incremental efficiency and impact of a spatially-targeted interventions used in combination with household contact tracing (HHCT). Our analysis reveals that HHCT is relatively efficient with a median of 40 (Interquartile Range: 31.7 to 49.9) household contacts required to be screened to detect a single case of active tuberculosis. However, HHCT has limited population impact, producing a median incidence reduction of only 3.7% (Interquartile Range: 5.8% to 1.9%) over 5 years. In comparison, spatially targeted screening (which we modeled as active case finding within high tuberculosis prevalence areas 100 m2 grid cell) is far less efficient, requiring evaluation of ≈12 times the number of individuals as HHCT to find a single individual with active tuberculosis. Furthermore, the addition of the spatially targeted screening effort produced only modest additional reductions in tuberculosis incidence over the 5 year period (≈1.3%) in tuberculosis incidence. In summary, we found that HHCT is an efficient approach for tuberculosis case finding, but has limited population impact. Other screening approaches which target areas of high tuberculosis prevalence are less efficient, and may have limited impact unless very large numbers of individuals can be screened. [ABSTRACT FROM AUTHOR]

The goal of tracing, testing, and quarantining contacts of infected individuals is to contain the spread of infectious diseases, a strategy widely used during the COVID-19 pandemic. However, limited research exists on the effectiveness of contact tracing, especially with regard to key performance indicators (KPIs), such as the proportion of cases arising from previously identified contacts. In our study, we analyzed contact tracing data from Belgium collected between September 2020 and December 2021 to assess the impact of contact tracing on SARS-CoV-2 transmission and understand its characteristics. Among confirmed cases involved in contact tracing in the Flemish and Brussels-Capital regions, 19.1% were previously identified as close contacts and were aware of prior exposure. These cases, referred to as 'known' to contact tracing operators, reported on average fewer close contacts compared to newly identified individuals (0.80 versus 1.05), resulting in fewer secondary cases (0.23 versus 0.28). Additionally, we calculated the secondary attack rate, representing infections per contact, which was on average lower for the 'known' cases (0.22 versus 0.25) between December 2020 and August 2021. These findings indicate the effectiveness of contact tracing in Belgium in reducing SARS-CoV-2 transmission. Although we were unable to quantify the exact number of prevented cases, our findings emphasize the importance of contact tracing as a public health measure. In addition, contact tracing data provide indications of potential shifts in transmission patterns among different age groups associated with emerging variants of concern and increasing vaccination rates. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, control measures, especially massive contact tracing following prompt quarantine and isolation, play an important role in mitigating the disease spread, and quantifying the dynamic contact rate and quarantine rate and estimate their impacts remain challenging. To precisely quantify the intensity of interventions, we develop the mechanism of physics-informed neural network (PINN) to propose the extended transmission-dynamics-informed neural network (TDINN) algorithm by combining scattered observational data with deep learning and epidemic models. The TDINN algorithm can not only avoid assuming the specific rate functions in advance but also make neural networks follow the rules of epidemic systems in the process of learning. We show that the proposed algorithm can fit the multi-source epidemic data in Xi'an, Guangzhou and Yangzhou cities well, and moreover reconstruct the epidemic development trend in Hainan and Xinjiang with incomplete reported data. We inferred the temporal evolution patterns of contact/quarantine rates, selected the best combination from the family of functions to accurately simulate the contact/quarantine time series learned by TDINN algorithm, and consequently reconstructed the epidemic process. The selected rate functions based on the time series inferred by deep learning have epidemiologically reasonable meanings. In addition, the proposed TDINN algorithm has also been verified by COVID-19 epidemic data with multiple waves in Liaoning province and shows good performance. We find the significant fluctuations in estimated contact/quarantine rates, and a feedback loop between the strengthening/relaxation of intervention strategies and the recurrence of the outbreaks. Moreover, the findings show that there is diversity in the shape of the temporal evolution curves of the inferred contact/quarantine rates in the considered regions, which indicates variation in the intensity of control strategies adopted in various regions. Author summary: When applying the compartment model to simulate the disease transmission dynamics, some parameters or particular functions are assumed to describe the intensity of the control interventions. However, these preset specific functions may not accurately quantify the intervention strategies, which brings great challenges to accurately make prediction and evaluation. In this study, we developed an extended transmission-dynamics-informed neural network algorithm by integrating deep neural network with epidemic model. Even for insufficient case data, the proposed algorithm can still help us reconstruct the temporal evolution trend of the epidemic and infer unknown parameters. We inferred the time series on contract rate and quarantine rate for six regions based on the case data, on which the reasonable and interpretable functions, describing the dynamic variation in the intensity of control strategies, can be successfully selected and determined. The inferred contact/quarantine rates in various regions show the diverse shapes and regional dependent, and hence the variation in the intensity of control measures. This suggests the dynamic zero-case policy exhibits the different efficacy in reducing contacts and increasing the quarantine and isolation. [ABSTRACT FROM AUTHOR]

The coronavirus disease (COVID-19) pandemic has led to an unprecedented public health crisis. Insufficient testing continues to limit the effectiveness of the global response to the COVID-19 pandemic. Molecular testing methods such as reverse transcriptase polymerase chain reaction (RT-PCR) continue to be highly centralized and are a sub-optimal option for population surveillance. Rapid antigen tests (Ag-RDTs) offer multiple benefits including low costs, high flexibility to conduct tests in a wide variety of settings, and faster return of results. Self-test Ag-RDTs (STs) have gained approval in several markets and offer the possibility to expand testing, reaching at-risk populations. While STs have the potential to assist the COVID-19 response, test result integrity, reporting, and appropriate linkage to care continue to hinder the widespread implementation of self-testing programs. This protocol presents a mixed-methods pragmatic trial (ISRCTN91602092) to better understand the feasibility of self-testing as part of a contact tracing strategy within the Brazilian public health system. Approximately 604 close contacts of 150 index cases testing positive for COVID-19 will be enrolled. Index cases will be randomized for their close contacts to participate in either serial (daily) self-testing over a 10-day follow-up period or a more traditional approach to contact tracing with a professional Ag-RDT at one time point post-exposure. Usability workshops and focus group discussions will also be conducted. This study protocol presents a comprehensive plan to assess the effectiveness, operational feasibility, and stakeholder preferences of a serial self-testing strategy for contact tracing within the Brazilian public health system. Our results will contribute to better understanding of the feasibility of a self-testing strategy within the public sector. Potential risks and limitations are discussed. Our findings will have important implications as governments continue working to mitigate the impact of COVID-19, particularly in the context of where to direct limited resources for testing and healthcare infrastructure. Registration: This trial is registered at ISCTRN (ISRCTN91602092). [ABSTRACT FROM AUTHOR]

China had conducted some of the most stringent public health measures to control the spread of successive SARS-CoV-2 variants. However, the effectiveness of these measures and their impacts on the associated disease burden have rarely been quantitatively assessed at the national level. To address this gap, we developed a stochastic age-stratified metapopulation model that incorporates testing, contact tracing and isolation, based on 419 million travel movements among 366 Chinese cities. The study period for this model began from September 2022. The COVID-19 disease burden was evaluated, considering 8 types of underlying health conditions in the Chinese population. We identified the marginal effects between the testing speed and reduction in the epidemic duration. The findings suggest that assuming a vaccine coverage of 89%, the Omicron-like wave could be suppressed by 3-day interval population-level testing (PLT), while it would become endemic with 4-day interval PLT, and without testing, it would result in an epidemic. PLT conducted every 3 days would not only eliminate infections but also keep hospital bed occupancy at less than 29.46% (95% CI, 22.73–38.68%) of capacity for respiratory illness and ICU bed occupancy at less than 58.94% (95% CI, 45.70–76.90%) during an outbreak. Furthermore, the underlying health conditions would lead to an extra 2.35 (95% CI, 1.89–2.92) million hospital admissions and 0.16 (95% CI, 0.13–0.2) million ICU admissions. Our study provides insights into health preparedness to balance the disease burden and sustainability for a country with a population of billions. Author summary: As China continues to be challenged by successive SARS-CoV-2 variants, rethinking population health, broader than health-care system alone, is a prerequisite for health preparedness. China has introduced several changes to its public health measures in response to evolving pandemic risk, however, the effectiveness of public health measures in controlling COVID-19 outbreaks in China and their impacts on the associated disease burden have not been quantitatively assessed at the national level. Here, we developed a stochastic age-stratified metapopulation model based on high resolution human mobility data to address these questions. Our results suggest that there's marginal effects between the testing speed and reduction in the epidemic duration. With a rapid implementation of population-level testing and a short response lag would be critical if aiming at suppression of potential future SARS-CoV-2 waves in China. Furthermore, the underlying health conditions would lead to extra hospital admissions and ICU admissions, where obesity is expected to contribute to most extra hospital admissions, while hypertension could contribute to most extra ICU admissions. [ABSTRACT FROM AUTHOR]

There are many contrasting results concerning the effectiveness of Test-Trace-Isolate (TTI) strategies in mitigating SARS-CoV-2 spread. To shed light on this debate, we developed a novel static-temporal multiplex network characterizing both the regular (static) and random (temporal) contact patterns of individuals and a SARS-CoV-2 transmission model calibrated with historical COVID-19 epidemiological data. We estimated that the TTI strategy alone could not control the disease spread: assuming R0 = 2.5, the infection attack rate would be reduced by 24.5%. Increased test capacity and improved contact trace efficiency only slightly improved the effectiveness of the TTI. We thus investigated the effectiveness of the TTI strategy when coupled with reactive social distancing policies. Limiting contacts on the temporal contact layer would be insufficient to control an epidemic and contacts on both layers would need to be limited simultaneously. For example, the infection attack rate would be reduced by 68.1% when the reactive distancing policy disconnects 30% and 50% of contacts on static and temporal layers, respectively. Our findings highlight that, to reduce the overall transmission, it is important to limit contacts regardless of their types in addition to identifying infected individuals through contact tracing, given the substantial proportion of asymptomatic and pre-symptomatic SARS-CoV-2 transmission. Author summary: Among the various targeted NPIs, the Test-Trace-Isolate (TTI) strategies have been commonly adopted to mitigate and control the spread of infectious diseases. Previous studies evaluating the effectiveness of TTI strategy on SARS-CoV-2 spreading have presented contrasting results, which could be due to the nature of observation studies and imperfect reflection of characteristics of the disease and interventions including TTI in the analyses. To properly account for the contact patterns, here we propose a novel static-temporal multiplex network model describing the static contacts and temporal contacts encountered in different settings (like households, schools, workplaces or general community), which captures the essential nature of social behavior relevant to transmission risk and enables us to assess the effectiveness of the TTI strategy. Our proposed model suggests that TTI strategy solely could not control the spread of SARS-CoV-2 and it should be combined with other social distancing policy to reduce the overall transmission of SARS-CoV-2. [ABSTRACT FROM AUTHOR]

Background: Rural U.S. communities are at risk from COVID-19 due to advanced age and limited access to acute care. Recognizing this, the Vashon Medical Reserve Corps (VMRC) in King County, Washington, implemented an all-volunteer, community-based COVID-19 response program. This program integrated public engagement, SARS-CoV-2 testing, contact tracing, vaccination, and material community support, and was associated with the lowest cumulative COVID-19 case rate in King County. This study aimed to investigate the contributions of demographics, geography and public health interventions to Vashon's low COVID-19 rates. Methods: This observational cross-sectional study compares cumulative COVID-19 rates and success of public health interventions from February 2020 through November 2021 for Vashon Island with King County (including metropolitan Seattle) and Whidbey Island, located ~50 km north of Vashon. To evaluate the role of demography, we developed multiple linear regression models of COVID-19 rates using metrics of age, race/ethnicity, wealth and educational attainment across 77 King County zip codes. To investigate the role of remote geography we expanded the regression models to include North, Central and South Whidbey, similarly remote island communities with varying demographic features. To evaluate the effectiveness of VMRC's community-based public health measures, we directly compared Vashon's success of vaccination and contact tracing with that of King County and South Whidbey, the Whidbey community most similar to Vashon. Results: Vashon's cumulative COVID-19 case rate was 29% that of King County overall (22.2 vs 76.8 cases/K). A multiple linear regression model based on King County demographics found educational attainment to be a major correlate of COVID-19 rates, and Vashon's cumulative case rate was just 38% of predicted (p <.05), so demographics alone do not explain Vashon's low COVID-19 case rate. Inclusion of Whidbey communities in the model identified a major effect of remote geography (-49 cases/K, p <.001), such that observed COVID-19 rates for all remote communities fell within the model's 95% prediction interval. VMRC's vaccination effort was highly effective, reaching a vaccination rate of 1500 doses/K four months before South Whidbey and King County and maintaining a cumulative vaccination rate 200 doses/K higher throughout the latter half of 2021 (p <.001). Including vaccination rates in the model reduced the effect of remote geography to -41 cases/K (p <.001). VMRC case investigation was also highly effective, interviewing 96% of referred cases in an average of 1.7 days compared with 69% in 3.7 days for Washington Department of Health investigating South Whidbey cases and 80% in 3.4 days for Public Health–Seattle & King County (both p<0.001). VMRC's public health interventions were associated with a 30% lower case rate (p<0.001) and 55% lower hospitalization rate (p = 0.056) than South Whidbey. Conclusions: While the overall magnitude of the pre-Omicron COVID-19 pandemic in rural and urban U.S. communities was similar, we show that island communities in the Puget Sound region were substantially protected from COVID-19 by their geography. We further show that a volunteer community-based COVID-19 response program was highly effective in the Vashon community, augmenting the protective effect of geography. We suggest that Medical Reserve Corps should be an important element of future pandemic planning. [ABSTRACT FROM AUTHOR]

A preemptive multi-hop contact tracing scheme that tracks not only the direct contacts of those who tested positive for COVID-19, but also secondary or tertiary contacts has been proposed and deployed in practice with some success. We propose a mathematical methodology for evaluating this preemptive contact tracing strategy that combines the contact tracing dynamics and the virus transmission mechanism in a single framework using microscopic Markov Chain approach (MMCA). We perform Monte Carlo (MC) simulations to validate our model and show that the output of our model provides a reasonable match with the result of MC simulations. Utilizing the formulation under a human contact network generated from real-world data, we show that the cost-benefit tradeoff can be significantly enhanced through an implementation of the multi-hop contact tracing as compared to traditional contact tracing. We further shed light on the mechanisms behind the effectiveness of the multi-hop testing strategy using the framework. We show that our mathematical framework allows significantly faster computation of key attributes for multi-hop contact tracing as compared to MC simulations. This in turn enables the investigation of these attributes for large contact networks, and constitutes a significant strength of our approach as the contact networks that arise in practice are typically large. [ABSTRACT FROM AUTHOR]

Background: Understanding the drivers of SARS-CoV-2 transmission can inform the development of interventions. We evaluated transmission identified by contact tracing investigations between March–May 2020 in Salt Lake County, Utah, to quantify the impact of this intervention and identify risk factors for transmission. Methods: RT-PCR positive and untested symptomatic contacts were classified as confirmed and probable secondary case-patients, respectively. We compared the number of case-patients and close contacts generated by different groups, and used logistic regression to evaluate factors associated with transmission. Results: Data were collected on 184 index case-patients and up to six generations of contacts. Of 1,499 close contacts, 374 (25%) were classified as secondary case-patients. Decreased transmission odds were observed for contacts aged <18 years (OR = 0.55 [95% CI: 0.38–0.79]), versus 18–44 years, and for workplace (OR = 0.36 [95% CI: 0.23–0.55]) and social (OR = 0.44 [95% CI: 0.28–0.66]) contacts, versus household contacts. Higher transmission odds were observed for case-patient's spouses than other household contacts (OR = 2.25 [95% CI: 1.52–3.35]). Compared to index case-patients identified in the community, secondary case-patients identified through contract-tracing generated significantly fewer close contacts and secondary case-patients of their own. Transmission was heterogeneous, with 41% of index case-patients generating 81% of directly-linked secondary case-patients. Conclusions: Given sufficient resources and complementary public health measures, contact tracing can contain known chains of SARS-CoV-2 transmission. Transmission is associated with age and exposure setting, and can be highly variable, with a few infections generating a disproportionately high share of onward transmission. [ABSTRACT FROM AUTHOR]

Introduction: Leprosy is a chronic mycobacterial disease of public health importance. It is one of the leading causes of permanent physical disability. The prevalence of leprosy in Ethiopia has remained stagnant over the last decades. The aim of the study was to identify new leprosy cases and trace household contacts at risk of developing leprosy by active case detection. The study area was Kokosa district, West Arsi zone, Oromia region, Ethiopia. Method: A prospective longitudinal study was conducted from June 2016-September 2018 at Kokosa district. Ethical approvals were obtained from all relevant institutions. Health extension workers screened households by house-to-house visits. Blood samples were collected and the level of anti-PGL-I IgM measured at two-time points. Results: More than 183,000 people living in Kokosa district were screened. Dermatologists and clinical nurses with special training on leprosy confirmed the new cases, and their household contacts were included in the study. Of the 91 new cases diagnosed and started treatment, 71 were recruited into our study. Sixty-two percent were males and 80.3% were multibacillary cases. A family history of leprosy was found in 29.6% of the patients with cohabitation ranging from 10 to 30 years. Eight new leprosy cases were diagnosed among the 308 household contacts and put on multi-drug therapy. The New Case Detection Rate increased from 28.3/100,000 to 48.3/100,000 between 2015/2016 and 2016/2017. Seventy one percent of leprosy patients and 81% of the household contacts' level of anti-PGL-I IgM decreased after treatment. In conclusion,the results of the study showed the importance of active case detection and household contact tracing. It enhances early case finding, and promotes early treatment, thereby interrupting transmission and preventing potential disability from leprosy. [ABSTRACT FROM AUTHOR]

Emerging infection diseases (EIDs) are an increasing threat to global public health, especially when the disease is newly emerging. Institutions of higher education (IHEs) are particularly vulnerable to EIDs because student populations frequently share high-density residences and strongly mix with local and distant populations. In fall 2020, IHEs responded to a novel EID, COVID-19. Here, we describe Quinnipiac University's response to SARS-CoV-2 and evaluate its effectiveness through empirical data and model results. Using an agent-based model to approximate disease dynamics in the student body, the University established a policy of dedensification, universal masking, surveillance testing via a targeted sampling design, and app-based symptom monitoring. After an extended period of low incidence, the infection rate grew through October, likely due to growing incidence rates in the surrounding community. A super-spreader event at the end of October caused a spike in cases in November. Student violations of the University's policies contributed to this event, but lax adherence to state health laws in the community may have also contributed. The model results further suggest that the infection rate was sensitive to the rate of imported infections and was disproportionately impacted by non-residential students, a result supported by the observed data. Collectively, this suggests that campus-community interactions play a major role in campus disease dynamics. Further model results suggest that app-based symptom monitoring may have been an important regulator of the University's incidence, likely because it quarantined infectious students without necessitating test results. Targeted sampling had no substantial advantages over simple random sampling when the model incorporated contact tracing and app-based symptom monitoring but reduced the upper boundary on 90% prediction intervals for cumulative infections when either was removed. Thus, targeted sampling designs for surveillance testing may mitigate worst-case outcomes when other interventions are less effective. The results' implications for future EIDs are discussed. [ABSTRACT FROM AUTHOR]

COVID-19 exposed and exacerbated health disparities, and a core challenge has been how to adapt pandemic response and public health in light of these disproportionate health burdens. Responding to this challenge, the County of Santa Clara Public Health Department designed a model of "high-touch" contact tracing that integrated social services with disease investigation, providing continued support and resource linkage for clients from structurally vulnerable communities. We report results from a cluster randomized trial of 5,430 cases from February to May 2021 to assess the ability of high-touch contact tracing to aid with isolation and quarantine. Using individual-level data on resource referral and uptake outcomes, we find that the intervention, randomized assignment to the high-touch program, increased the referral rate to social services by 8.4% (95% confidence interval, 0.8%-15.9%) and the uptake rate by 4.9% (-0.2%-10.0%), with the most pronounced increases in referrals and uptake of food assistance. These findings demonstrate that social services can be effectively combined with contact tracing to better promote health equity, demonstrating a novel path for the future of public health. [ABSTRACT FROM AUTHOR]

Although some methods for estimating the instantaneous reproductive number during epidemics have been developed, the existing frameworks usually require information on the distribution of the serial interval and/or additional contact tracing data. However, in the case of outbreaks of emerging infectious diseases with an unknown natural history or undetermined characteristics, the serial interval and/or contact tracing data are often not available, resulting in inaccurate estimates for this quantity. In the present study, a new framework was specifically designed for joint estimates of the instantaneous reproductive number and serial interval. Concretely, a likelihood function for the two quantities was first introduced. Then, the instantaneous reproductive number and the serial interval were modeled parametrically as a function of time using the interpolation method and a known traditional distribution, respectively. Using the Bayesian information criterion and the Markov Chain Monte Carlo method, we ultimately obtained their estimates and distribution. The simulation study revealed that our estimates of the two quantities were consistent with the ground truth. Seven data sets of historical epidemics were considered and further verified the robust performance of our method. Therefore, to some extent, even if we know only the daily incidence, our method can accurately estimate the instantaneous reproductive number and serial interval to provide crucial information for policymakers to design appropriate prevention and control interventions during epidemics. Author summary: Contagious disease epidemics, such as coronavirus disease 2019 (COVID-19), intermittently threaten global public health. In this situation, policymakers usually hope to timely monitor the severity of the disease transmission and thus evaluate the effectiveness of the prevention and control interventions. Instantaneous reproductive number and serial interval are the two most commonly used monitoring indices. The former refers to the expected number of secondary cases infected by a primary case, and the latter refers to the time interval between a primary case presenting with symptoms and its secondary cases developing symptoms. However, the existing frameworks can hardly estimate these two indicators simultaneously in the absence of additional contact tracing data or other prior information. In the presented study, we developed a likelihood method incorporating interpolation, Bayesian information criterion and Markov Chain Monte Carlo method to jointly estimate the two quantities, which only depends on the daily incidence. The simulation study and several data sets of historical epidemics verified the robust performance of our method. Therefore, even in the case of outbreaks of emerging infectious diseases with an unknown natural history or undetermined characteristics, our method can, to a certain extent, provide crucial information for policymakers to design appropriate measures during epidemics. [ABSTRACT FROM AUTHOR]

With countries across the world facing repeated epidemic waves, it becomes critical to monitor, mitigate and prevent subsequent waves. Common indicators like active case numbers may not be sensitive enough in the presence of systemic inefficiencies like insufficient testing or contact tracing. Test positivity rates are sensitive to testing strategies and cannot estimate the extent of undetected cases. Reproductive numbers estimated from logarithms of new incidences are inaccurate in dynamic scenarios and not sensitive enough to capture changes in efficiencies. Systemic fatigue results in lower testing, inefficient tracing and quarantining thereby precipitating the onset of the epidemic wave. We propose a novel indicator for detecting the slippage of test-trace efficiency based on the number of deaths/hospitalizations resulting from known and hitherto unknown infections. This can also be used to forecast an epidemic wave that is advanced or exacerbated due to a drop in efficiency in situations where the testing has come down drastically and contact tracing is virtually nil as is prevalent currently. Using a modified SEIRD epidemic simulator we show that (i) Ratio of deaths/hospitalizations from an undetected infection to total deaths converges to a measure of systemic test-trace inefficiency. (ii) This index forecasts the slippage in efficiency earlier than other known metrics. (iii) Mitigation triggered by this index helps reduce peak active caseload and eventual deaths. Deaths/hospitalizations accurately track the systemic inefficiencies and detect latent cases. Based on these results we make a strong case that administrations use this metric in the ensemble of indicators. Further, hospitals may need to be mandated to distinctly register deaths/hospitalizations due to previously undetected infections. Thus the proposed metric is an ideal indicator of an epidemic wave that poses the least socio-economic cost while keeping the surveillance robust during periods of pandemic fatigue. [ABSTRACT FROM AUTHOR]

The objective of this study was to assess COVID-19 classroom transmission in the university setting when physical distancing was eliminated. Data was collected in fall 2021 at a private university. Universal masking, robust contact tracing, vaccination requirement, and enforced testing were in place. Exposures were classified as classroom versus non-classroom. ANOVA and chi-squared tests were used to identify significant relationships between predictors and COVID-19 test result. Logistic regression was conducted to investigate the relationship between exposure type and test result. A total of 162 student cases were identified with 1,658 associated close contacts. One-third of contacts (31.1%, n = 516) only had a non-classroom exposure, 63.8% (n = 1,057) only had a classroom exposure, and 5.1% (n = 85) had both. Close contacts were significantly more likely to test positive if they had a non-classroom exposure (60 of 601; 10.0%) compared to a classroom exposure (1 of 1057; 0.1%) (OR 58.8, CI 18.5–333.3, p < 0.001). Removing physical distancing in classrooms that had universal masking did not result in high rates of COVID-19 transmission. This has policy implications because eliminating physical distancing does not greatly increase transmission risk when universal masking is in place. [ABSTRACT FROM AUTHOR]

A major limiting factor in combatting the HIV epidemic has been the identification of people living with HIV. Index testing programs were developed to face that challenge. Index testing is a focused HIV testing service approach in which family members and partners of people living with HIV are offered testing. Despite the implementation of index testing, there is still a gap between the estimated number of people living with HIV and those who know their status in Côte d'Ivoire. This study aimed to understand the implementation process of index testing in Côte d'Ivoire and to identify implementation challenges from healthcare workers perspectives. In January and February 2020, we conducted a qualitative study through 105 individual semi-structured interviews regarding index testing with clinical providers (physicians, nurses, and midwives) and non-clinical providers (community counselors and their supervisors) at 16 rural health facilities across four regions of Côte d'Ivoire. We asked questions regarding the index testing process, index client intake, contact tracing and testing, the challenges of implementation, and solicited recommendations on improving index testing in Côte d'Ivoire. The interviews revealed that index testing is implemented by non-clinical providers. Passive referral, by which the index client brought their contact to be tested, and providers referral, by which a healthcare worker reached out to the index client's contact, were the preferred contact tracing and testing strategies. There was not statistically significant difference between immediate and delayed notification. Reported challenges of index testing implementation included index cases refusing to give their partner's information or a partner refusing to be tested, fear of divorce, societal stigma, long distances, lack of appropriate training in index testing strategies, and lack of a private room for counseling. The recommendations given by providers to combat these was to reinforce HIV education among the population, to train healthcare workers on index testing strategies, and to improve infrastructure, transportation, and communication resources. The study showed that the elements that influenced the process of index testing in Côte d'Ivoire were multifactorial, including individual, interpersonal, health systems, and societal factors. Thus, a multi-faceted approach to overcoming challenges of index testing in Côte d'Ivoire is needed to improve the yield of index testing. [ABSTRACT FROM AUTHOR]

We critically appraised the literature regarding in-flight transmission of a range of respiratory infections to provide an evidence base for public health policies for contact tracing passengers, given the limited pathogen-specific data for SARS-CoV-2 currently available. Using PubMed, Web of Science, and other databases including preprints, we systematically reviewed evidence of in-flight transmission of infectious respiratory illnesses. A meta-analysis was conducted where total numbers of persons on board a specific flight was known, to calculate a pooled Attack Rate (AR) for a range of pathogens. The quality of the evidence provided was assessed using a bias assessment tool developed for in-flight transmission investigations of influenza which was modelled on the PRISMA statement and the Newcastle-Ottawa scale. We identified 103 publications detailing 165 flight investigations. Overall, 43.7% (72/165) of investigations provided evidence for in-flight transmission. H1N1 influenza A virus had the highest reported pooled attack rate per 100 persons (AR = 1.17), followed by SARS-CoV-2 (AR = 0.54) and SARS-CoV (AR = 0.32), Mycobacterium tuberculosis (TB, AR = 0.25), and measles virus (AR = 0.09). There was high heterogeneity in estimates between studies, except for TB. Of the 72 investigations that provided evidence for in-flight transmission, 27 investigations were assessed as having a high level of evidence, 23 as medium, and 22 as low. One third of the investigations that reported on proximity of cases showed transmission occurring beyond the 2x2 seating area. We suggest that for emerging pathogens, in the absence of pathogen-specific evidence, the 2x2 system should not be used for contact tracing. Instead, alternate contact tracing protocols and close contact definitions for enclosed areas, such as the same cabin on an aircraft or other forms of transport, should be considered as part of a whole of journey approach. [ABSTRACT FROM AUTHOR]

Background: Interferon-γ (IFN-γ) is a key cytokine inducing protective immune responses during tuberculosis (TB) infection. Helminth-induced immune responses may affect IFN-γ production by T cells, although its connection with disease severity and immune recovery during treatment is unexplored. We investigated the species-specific effect of helminths on the IFN-γ production by T cells in relation to disease severity during active and latent TB infection (LTBI). Methods: In this study, 69 active pulmonary TB patients (PTB), 28 with LTBI and 66 healthy controls were included. Active TB was diagnosed using GenXpert MTB/RIF while QuantiFERON test (QFT) was used for the screening of healthy community controls (CCs) and for the diagnosis of LTBI. Helminth infection was identified by routine diagnosis whereas clinical disease severity was evaluated by the TB score. Intracellular IFN-γ production of T cells in stimulated peripheral blood mononuclear cells (PBMCs) was analyzed by flow cytometry using TB antigens (PPD), the polyclonal T cell activator staphylococcal enterotoxin B (SEB), or medium as unstimulated control. Results: Helminth infected CCs and LTBI subjects showed a significant reduction of IFN-γ+ CD4+ T cells by PPD-stimulation compared to non-helminth infected control groups. The significant reduction in the frequency of IFN-γ+ T cells in both latent and active PTB patients following SEB stimulation was mostly attributed to Schistosoma mansoni infection, whereas Ascaris lumbricoides, Schistosoma mansoni, and hookworm infection contributed equally in CCs. Following anti-helminthic and anti-TB treatment for 2 months, the frequency of IFN-γ+ CD4 T cells in helminth coinfected PTB was restored to levels of helminth negative PTB before treatment. Helminth coinfected PTB patients with an intermediate and severe clinical course had reduced capacity for production of IFN-γ+ T cells compared to the corresponding non-helminth infected PTB. Conclusion: We found a reduction in IFN-γ producing T cells by helminth coinfection which was restored following anti-helminthic treatment. This reduction was helminth species-dependent in an exploratory sub-analysis and correlated to increased disease severity. Author summary: Protective immunity against tuberculosis (TB) requires a Th-1 response with cytokines like TNF and IFN-γ which plays a key role in the recruitment and activation of immune cells. Helminth infection, on the other hand, can lead to induction of regulatory T cells and a Th-2 skewed response decreasing IFN-γ in T cells. Decreased Th-1 responses could favor reactivation of latent TB infection (LTBI), although the helminth species-specific effect on IFN-γ+CD4+ T cells and the link to TB disease severity in patients with active pulmonary TB (PTB) have not been fully investigated. Therefore, blood cells (PBMCs) from healthy controls, LTBI individuals, and PTB patients were used to evaluate the impact of different helminths on the frequency of IFN-γ+CD4+ T cells, in Gondar Ethiopia. Ascaris lumbricoides, Schistosoma mansoni, and hookworm infection in healthy controls contributed equally to decreasing the frequency of IFN-γ+CD4+ T cells, whereas in both LTBI and PTB patients S. mansoni coinfection had the greatest impact on reducing IFN-γ producing capacity of T cells. Decreased IFN-γ producing capacity of T cells was correlated with increased TB disease severity, only in helminth coinfected PTB patients, and anti-helminthic therapy restored the IFN-γ producing capacity of T cells at the 2 months follow-up. [ABSTRACT FROM AUTHOR]

Background: The recent outbreaks of Ebola virus disease (EVD) in Uganda and the Marburg virus disease (MVD) in Ghana reflect a persisting threat of Filoviridae to the global health community. Characteristic of Filoviridae are not just their high case fatality rates, but also that corpses are highly contagious and prone to cause infections in the absence of appropriate precautions. Vaccines against the most virulent Ebolavirus species, the Zaire ebolavirus (ZEBOV) are approved. However, there exists no approved vaccine or treatment against the Sudan ebolavirus (SUDV) which causes the current outbreak of EVD. Hence, the control of the outbreak relies on case isolation, safe funeral practices, and contact tracing. So far, the effectiveness of these control measures was studied only separately by epidemiological models, while the impact of their interaction is unclear. Methods and findings: To sustain decision making in public health-emergency management, we introduce a predictive model to study the interaction of case isolation, safe funeral practices, and contact tracing. The model is a complex extension of an SEIR-type model, and serves as an epidemic preparedness tool. The model considers different phases of the EVD infections, the possibility of infections being treated in isolation (if appropriately diagnosed), in hospital (if not properly diagnosed), or at home (if the infected do not present to hospital for whatever reason). It is assumed that the corpses of those who died in isolation are buried with proper safety measures, while those who die outside isolation might be buried unsafely, such that transmission can occur during the funeral. Furthermore, the contacts of individuals in isolation will be traced. Based on parameter estimates from the scientific literature, the model suggests that proper diagnosis and hence isolation of cases has the highest impact in reducing the size of the outbreak. However, the combination of case isolation and safe funeral practices alone are insufficient to fully contain the epidemic under plausible parameters. This changes if these measures are combined with contact tracing. In addition, shortening the time to successfully trace back contacts contribute substantially to contain the outbreak. Conclusions: In the absence of an approved vaccine and treatment, EVD management by proper and fast diagnostics in combination with epidemic awareness are fundamental. Awareness will particularly facilitate contact tracing and safe funeral practices. Moreover, proper and fast diagnostics are a major determinant of case isolation. The model introduced here is not just applicable to EVD, but also to other viral hemorrhagic fevers such as the MVD or the Lassa fever. [ABSTRACT FROM AUTHOR]

Differences in national responses to COVID-19 have been associated with the cultural value of collectivism. The present research builds on these findings by examining the relationship between collectivism at the individual level and adherence to public health recommendations to combat COVID-19 during the pre-vaccination stage of the pandemic, and examines different characteristics of collectivism (i.e., concern for community, trust in institutions, perceived social norms) as potential psychological mechanisms that could explain greater compliance. A study with a cross-section of American participants (N = 530) examined the relationship between collectivism and opting-in to digital contact tracing (DCT) and wearing face coverings in the general population. More collectivistic individuals were more likely to comply with public health interventions than less collectivistic individuals. While collectivism was positively associated with the three potential psychological mechanisms, only perceived social norms about the proportion of people performing the public health interventions explained the relationship between collectivism and compliance with both public health interventions. This research identifies specific pathways by which collectivism can lead to compliance with community-benefiting public health behaviors to combat contagious diseases and highlights the role of cultural orientation in shaping individuals' decisions that involve a tension between individual cost and community benefit. [ABSTRACT FROM AUTHOR]

Genomic surveillance and wastewater tracking strategies were used to strengthen the public health response to an outbreak of the SARS-CoV-2 Delta AY.25 lineage associated with a university campus in Arizona. Epidemiologic and clinical data routinely gathered through contact tracing were matched to SARS-CoV-2 genomes belonging to an outbreak of AY.25 identified through ongoing phylogenomic analyses. Continued phylogenetic analyses were conducted to further describe the AY.25 outbreak. Wastewater collected twice weekly from sites across campus was tested for SARS-CoV-2 by RT-qPCR, and subsequently sequenced to identify variants. The AY.25 outbreak was defined by a single mutation (C18804T) and comprised 379 genomes from SARS-CoV-2 positive cases associated with the university and community. Several undergraduate student gatherings and congregate living settings on campus likely contributed to the rapid spread of COVID-19 across the university with secondary transmission into the community. The clade defining mutation was also found in wastewater samples collected from around student dormitories a week before the semester began, and 9 days before cases were identified. Genomic, epidemiologic, and wastewater surveillance provided evidence that an AY.25 clone was likely imported into the university setting just prior to the onset of the Fall 2021 semester, rapidly spread through a subset of the student population, and then subsequent spillover occurred in the surrounding community. The university and local public health department worked closely together to facilitate timely reporting of cases, identification of close contacts, and other necessary response and mitigation strategies. The emergence of new SARS-CoV-2 variants and potential threat of other infectious disease outbreaks on university campuses presents an opportunity for future comprehensive One Health genomic data driven, targeted interventions. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, digital contact-tracing has been employed in many countries to monitor and manage the spread of the disease. However, to be effective such a system must be adopted by a substantial proportion of the population; therefore, public trust plays a key role. This paper examines the NHS COVID-19 smartphone app, the digital contact-tracing solution in the UK. A series of interviews were carried out prior to the app's release (n = 12) and a large scale survey examining attitudes towards the app (n = 1,001) was carried out after release. Extending previous work reporting high level attitudes towards the app, this paper shows that prevailing negative attitudes prior to release persisted, and affected the subsequent use of the app. They also show significant relationships between trust, app features, and the wider social and societal context. There is lower trust amongst non-users of the app and trust correlates to many other aspects of the app, a lack of trust could hinder adoption and effectiveness of digital contact-tracing. The design of technology requiring wide uptake, e.g., for public health, should embed considerations of the complexities of trust and the context in which the technology will be used. [ABSTRACT FROM AUTHOR]

Background: The role of school contacts in the spread of the virus and the effectiveness of school closures in controlling the epidemic is still debated. We aimed to quantify the risk of transmission of SARS-CoV-2 in the school setting by type of school, characteristics of the index case and calendar period in the Province of Reggio Emilia (RE), Italy. The secondary aim was to estimate the speed of implementation of contact tracing. Methods: A population-based analysis of surveillance data on all COVID-19 cases occurring in RE, Italy, from 1 September 2020, to 4 April 2021, for which a school contact and/or exposure was suspected. An indicator of the delay in contact tracing was calculated as the time elapsed since the index case was determined to be positive and the date on which the swab test for classmates was scheduled (or most were scheduled). Results: Overall, 30,184 and 13,608 contacts among classmates and teachers/staff, respectively, were identified and were recommended for testing, and 43,214 (98.7%) underwent the test. Secondary transmission occurred in about 40% of the investigated classes, and the overall secondary case attack rate was 4%. This rate was slightly higher when the index case was a teacher but with almost no differences by type of school, and was stable during the study period. Speed of implementation of contact tracing increased during the study period, with the time from index case identification to testing of contacts being reduced from seven to three days. The ability to identify the possible source of infection in the index case also increased. Conclusions: Despite the spread of the Alpha variant during the study period in RE, the secondary case attack rate remained stable from school reopening in September 2020 until the beginning of April 2021. [ABSTRACT FROM AUTHOR]

Background: In November 2019, an outbreak of Lassa Fever occurred among health workers in a non-endemic district in Sierra Leone. The outbreak resulted in five cases, including two that were exported to the Netherlands. The outbreak tested multiple technical capacities in the International Health Regulations (2005) in a real-life setting. As such, an after action review (AAR) was undertaken as recommended by World Health Organization. We report on the findings of the AAR including best practices and lessons learnt. Methods: A two stage review process was employed. The first stage involved national pillar level reviews for each technical pillar and one review of the district level response. The second stage brought together all pillars, including participants from the national and sub-national level as well as health sector partners. National guidelines were used as references during the deliberations. A standardized template was used to report on the key findings on what happened, what was supposed to happen, what went well and lessons learnt. Results: This was a hospital associated outbreak that likely occurred due to a breach in infection prevention and control (IPC) practices resulting in three health workers being infected during a surgical operation. There was a delay in detecting the outbreak on time due to low index of suspicion among clinicians. Once detected, the outbreak response contained the outbreak within one incubation period. Areas that worked well included coordination, contact tracing, active case search and ring IPC. Notable gaps included delays in accessing local emergency funding and late distribution of IPC and laboratory supplies. Conclusions: The incident management system worked optimally to contain this outbreak. The core technical gaps identified in surveillance, IPC and delay in deployment of resources should be addressed through systemic changes that can mitigate future outbreaks. Author summary: The International Health Regulations (IHR) Monitoring and Evaluation Framework was developed by the World Health Organization to provide strategies to monitor and assess how countries are building their core public health capacities under IHR (2005). The framework has four components: annual reporting on IHR capacities (mandatory), Joint External Evaluation, simulation exercises and After Action Review (AAR). In November 2019, an outbreak of Lassa Fever occurred among health workers in a non-endemic district in Sierra Leone. The outbreak resulted in five cases, including two deaths and two exported cases to the Netherlands. The outbreak tested multiple technical capacities in the IHR (2005) in a real-life setting. We therefore conducted an AAR to assess how well the country responded to the outbreak. This hospital associated outbreak likely occurred due to a breach in infection prevention and control (IPC) practices. The response launched after detection of the outbreak successfully contained the outbreak within one incubation period. Areas that worked well included coordination, contact tracing, active case search and ring IPC. Areas that needed improvement were clinicians' knowledge on Lassa Fever, delays in accessing local emergency funding and late distribution of IPC and laboratory supplies. [ABSTRACT FROM AUTHOR]

Background: Ethiopia enforced extremely rigorous contact tracing and mandatory quarantine for all suspected contact and travelers entering the country for a period of 14-days duration during the early phases of the COVID-19 outbreak. Several studies investigated the experience of quarantined people because of COVID-19 or previous outbreaks. However, quarantine is often perceived differently in different cultures because of its historical association with class, gender, ethnicity, politics, and prejudices. To our knowledge, there is limited literature on quarantine experience in Ethiopia related to either COVID-19 or other infectious diseases. Therefore, this study was aimed to explore quarantine experience of people in Southern Nations Nationalities and Peoples' Region (SNNPR) of Ethiopia during early phase of COVID-19 pandemic. Methods: The study implemented an exploratory qualitative research design using a phenomenological approach. Face-to-face in-depth interviews were conducted with purposively recruited 29 respondents. Digitally recorded audio files have been listened to several times and verbatim transcriptions were done. The transcribed narratives were examined independently and content analysis was carried out through reading and re-reading the verbatim several times, open coding, grouping, categorizing, and abstracting the final themes. Results: Three broad themes were identified and characterized the experiences of quarantined people due to COVID-19. These themes were a) handling of the suspected person, b) adverse effects of quarantine and c) coping strategies. In addition, quarantine refusals; injustice in quarantine; quarantine errors; psychological distress; physiological changes; social effects; financial losses; personal and social coping strategies were the emerged sub-themes. Conclusions: This study explored a range of complex experiences of quarantined people because of the COVID-19 outbreak in SNNPR. The quarantined people included in this study were adversely affected psychologically, physiologically, socially, and economically. They also experienced quarantine errors and injustice. There is a need to gather clear justification for close contact before forcing the suspect for mandatory quarantine. In addition, there is a need to develop risk communication strategy to approach suspected contacts for quarantine. Moreover, assessing psychological, physiological, social, and economic impacts of quarantine on the individuals while they are in quarantine and after release could be important. The use of personal and social coping strategies including psychosocial support may lessen the adverse impacts of the quarantine. [ABSTRACT FROM AUTHOR]

The Indonesian government has issued various policies to control COVID-19. However, COVID-19 new cases continued to increase, and there remain uncertainties as to the future trajectory. We aimed to investigate how medical and health academics view the Indonesian government's handling of COVID-19 and which areas of health systems need to be prioritized to improve the government's response to COVID-19. We conducted a modified Delphi study adapting the COVID-19 assessment scorecard (COVID-SCORE) as the measurement criteria. We invited medical and health academics from ten universities across Indonesia to take part in the two-round Delphi study. In the first round, participants were presented with 20 statements of COVID-SCORE and asked to rate their agreement with each statement using a five-point Likert scale. All participants who completed the first cycle were invited to participate in the second cycle. They had the opportunity to revise their answers based on the previous cycle's results and ranked a list of actions to improve government response. We achieved a moderate consensus level for five statements, a low consensus level for 13 statements and no consensus for two statements. The prioritization suggested that top priorities for improving the government's response to COVID-19 in Indonesia encompass: (1) strengthening capacity to ensure consistent, credible and targeted communication while adopting a more inclusive and empathic communication style to address public concerns; (2) ensuring universal access to reliable COVID-19 testing by expanding lab infrastructure, facilitating operational readiness, and scaling up implementation of proven alternative/complementary tests to RT-PCR; and (3) boosting contact tracing implementation capacity and facilitating contact tracing for all positive cases, involving key stakeholders in further development of the existing contact tracing system (i.e. PeduliLindungi) as well as its evaluation and quality assurance. Ultimately, our study highlights the importance of strengthening health system functions during the pandemic and improving health system resilience for dealing with future public health emergencies. [ABSTRACT FROM AUTHOR]

Background: The unwillingness to share contacts is one of the least explored aspects of the COVID-19 pandemic. Here we report the factors associated with resistance to collaborate on contact tracing, based on the results of a nation-wide survey conducted in Italy in January-March 2021. Methods and findings: The repeated cross-sectional on-line survey was conducted among 7,513 respondents (mean age 45.7, 50.4% women) selected to represent the Italian adult population 18–70 years old. Two groups were defined based on the direct question response expressing (1) unwillingness or (2) willingness to share the names of individuals with whom respondents had contact. We selected 70% of participants (training data set) to produce several multivariable binomial generalized linear models and estimated the proportion of variation explained by the model by McFadden R2, and the model's discriminatory ability by the index of concordance. Then, we have validated the regression models using the remaining 30% of respondents (testing data set), and identified the best performing model by removing the variables based on their impact on the Akaike information criterion and then evaluating the model predictive accuracy. We also performed a sensitivity analysis using principal component analysis. Overall, 5.5% of the respondents indicated that in case of positive SARS-CoV-2 test they would not share contacts. Of note, this percentage varied from 0.8% to 46.5% depending on the answers to other survey questions. From the 139 questions included in the multivariable analysis, the initial model proposed 20 independent factors that were reduced to the 6 factors with only modest changes in the model performance. The 6-variables model demonstrated good performance in the training (c-index 0.85 and McFadden R2 criteria 0.25) and in the testing data set (93.3% accuracy, AUC 0.78, sensitivity 30.4% and specificity 97.4%). The most influential factors related to unwillingness to share contacts were the lack of intention to perform the test in case of contact with a COVID-19 positive individual (OR 5.60, 95% CI 4.14 to 7.58, in a fully adjusted multivariable analysis), disagreement that the government should be allowed to force people into self-isolation (OR 1.79, 95% CI 1.12 to 2.84), disagreement with the national vaccination schedule (OR 2.63, 95% CI 1.86 to 3.69), not following to the preventive anti-COVID measures (OR 3.23, 95% CI 1.85 to 5.59), the absence of people in the immediate social environment who have been infected with COVID-19 (1.66, 95% CI 1.24 to 2.21), as well as difficulties in finding or understanding the information about the infection or related recommendations. A limitation of this study is the under-representation of persons not participating in internet-based surveys and some vulnerable groups like homeless people, persons with disabilities or migrants. Conclusions: Our analysis revealed several groups that expressed unwillingness to collaborate on contact tracing. The identified patterns may play a principal role not only in the COVID-19 epidemic but also be important for possible future public health threats, and appropriate interventions for their correction should be developed and ready for the implementation. [ABSTRACT FROM AUTHOR]

Background: Google and Apple's Exposure Notifications System (ENS) was developed early in the COVID-19 pandemic to complement existing contact tracing efforts while protecting user privacy. An analysis by the Associated Press released in December 2020 estimated approximately 1 in 14 people had downloaded apps in states one was available. In this study, we assessed the motivation and experience of individuals who downloaded ENS apps from the Google Play and Apple App Stores. Methods: We collected review text, star rating, and date of rating for all the reviews on ENS apps in the Google Play and Apple App stores. We extracted the relative frequency of single words and phrases from reviews and created an open vocabulary language, with themes categorized by the research team, to study the salient themes around reviews with high (3–5 stars), neutral (3 stars), and negative (1–2 stars) ratings using logistic regression. Results: Of 7622 reviews obtained from 26 states between 04/07/2020 to 03/31/2021, 6364 were from Google Play Store, and 1258 were from Apple App Store. We obtained reviews for a total of 38 apps, with 25 apps from the Google Play Store and 13 apps from the Apple Play Store. 78% of the reviews are either 1 star or 5 stars. Positive reviews were driven by ease of use, support for the state government in creating the app, and encouragement for others to download, as well as engage in other COVID-19 precautions. Negative and neutral reviews focused on issues with app functionality (i.e., installation and tracking errors). Conclusions: Uptake was the largest barrier to success for ENS apps, but states can use insight from app store reviews to better position themselves if they choose to develop further public health apps. [ABSTRACT FROM AUTHOR]

Background: Household contact tracing provides TB screening and TB preventive therapy (TPT) to contacts at high risk of TB disease. However, it is resource intensive, inconvenient, and often poorly implemented. We investigated a novel model aiming to improve uptake. Methods: Between May and December 2014, we randomised patient with TB who consented to participate in the trial to either standard of care (SOC) or intervention (PACTS) arms. Participants randomised to PACTS received one screening/triage tool (adapted from WHO integrated management of adolescent and adult illnesses [IMAI] guidelines) and sputum pots for each reported household contact. The tool guided participants through symptom screening; TPT (6-months of isoniazid) eligibility; and sputum collection for contacts. Patients randomised to SOC were managed in accordance with national guidelines, that is, they received verbal instruction on who to bring to clinics for investigation using national guidelines. Main outcome and measures: The primary outcome was the proportion of adult contacts receiving treatment for TB within 3 months of randomisation. Secondary outcomes were the proportions of child contacts under age 5 years (U5Y) who were commenced on, and completed, TPT. Data were analyzed by logistic regression with random effects to adjust for household clustering. Results: Two hundred and fourteen index TB participants were block-randomized from two sites (107 PACTS, reporting 418 contacts; and 107 SOC, reporting 420 contacts). Overall, 62.8% of index TB participants were HIV-positive and 52.1% were TB culture-positive. 250 otherwise eligible TB patients declined participation and 6 households (10 PACTS, 6 SOC) were lost to follow-up and were not included in the analysis. By three months, nine contacts (PACTS: 6, [1.4%]; SOC: 3, [0.7%]) had TB diagnosed, with no difference between groups (adjusted odds ratio [aOR]: 2.18, 95% CI: 0.60–7.95). Eligible PACTS contacts (37/96, 38.5%) were more likely to initiate TPT by 3-months compared to SOC contacts (27/101, 26.7%; aOR 2.27, 95% CI: 1.04–4.98). U5Y children in the PACTS arm (47/81 58.0%) were more likely to have initiated TPT before the 3-month visit compared to SOC children (36/89, 41.4%; aOR: 2.31, 95% CI: 1.05–5.06). Conclusions and relevance: A household-centred patient-delivered symptom screen and IPT eligibility assessment significantly increased timely TPT uptake among U5Y children, but did not significantly increase TB diagnosis. This model needs to be optimized for acceptability, given low participation, and investigated in other low resource settings. Clinical trial registration: TRIAL REGISTRATION NUMBER: ISRCTN81659509 https://www.isrctn.com/ISRCTN81659509?q=&filters=conditionCategory:Respiratory,recruitmentCountry:Malawi,ageRange:Mixed&sort=&offset=1&totalResults=1&page=1&pageSize=10&searchType=basic-search. 19 July 2012. [ABSTRACT FROM AUTHOR]

Approximately 1.29 million COVID-19 cases involving healthcare workers (HCWs) have been reported globally, leading to several hospitals conducting mass testing for early detection of infected HCWs. This study was conducted to report our experience and findings from the mass testing of HCWs from a public hospital in Sabah, Malaysia. The mass testing was conducted from 1st March 2020 to 30th June 2020, and involved self-reported data and laboratory results of 2089 HCWs. All HCWs who took at least two nasopharyngeal swabs for COVID-19 testing at two different time intervals during the study period were included. Throughout the mass testing period, various strategies such as practices of the new norm, daily temperature and symptom checking, wearing of appropriate personal protective equipment (PPE), identification of high-risk areas and travel declaration of staffs were within the hospital for prevention of COVID-19 transmission. We observed a small percentage of COVID-19 infected HCWs (n = 19, 0.91%) from the mass testing. Both symptomatic and asymptomatic COVID-19 HCWs were almost equal in number. A majority of those infected were nurses (n = 16, 0.77%) who had contact exposure to COVID-19 positive person or person under investigation (PUI) (n = 15, 0.72%). Four of the COVID-19 infected HCWs (n = 4/19, 21.05%) had no contact exposure. These HCWs were not identified through contact tracing. Fortunately, they were detected during the mass testing and were isolated promptly. In conclusion, mass testing of HCWs helped in early identification of COVID-19 infected HCWs not identified through contact tracing. Strategies such as stratified mass testing, strict compliance to new norm, appropriate PPE usage and identification of high-risk area were effective in the prevention of COVID-19 infection among HCWs. [ABSTRACT FROM AUTHOR]

Despite that the impact of different helminth species is not well explored, the current dogma states that helminths affect the Th1/Th2 balance which in turn affects the risk of tuberculosis (TB) reactivation and severity of disease. We investigated the influence of helminth species on cytokine profiles including IL-17A in TB patients and healthy community controls (CCs). In total, 104 newly diagnosed pulmonary TB patients and 70 HIV negative and QuantiFERON negative CCs in Gondar, Ethiopia were included following helminth screening by stool microscopy. Plasma samples and ex vivo stimulation of peripheral blood mononuclear cells (PBMCs) with purified protein derivative (PPD) and Staphylococcus enterotoxin B (SEB) was used to determine cytokine profiles by cytometric bead array. In CCs, Ascaris lumbricoides or Schistosoma mansoni infections were associated with an impaired Th1-type response (IFN-gamma, IL-6 and TNF-alpha) in PBMCs mainly with SEB stimulations, whereas in TB patients only hookworm infection showed a similar pattern. Among CCs, the IL-17A response in PBMCs stimulated with SEB was higher only for S. mansoni, whereas in TB patients, the elevated systemic IL-17A plasma level was significantly suppressed in hookworm infected TB patients compared to patients without helminth coinfection. Following treatment of TB and helminth infection there was a general decrease in ex vivio IL-10 and TNF-alpha production in unstimulated, PPD or SEB stimulated PBMCs that was the most pronounced and significant in TB patients infected with S. mansoni, whereas the follow-up levels of IFN-gamma and IL-17A was significantly increased only in TB patients without helminth coinfection from PBMCs stimulated mainly with SEB. In summary, in addition to confirming helminth specific effects on the Th1/Th2 response before and after TB treatment, our novel finding is that IL-17A was impaired in helminth infected TB patients especially for hookworm, indicating a helminth species-specific immunoregulatory effect on IL-17A which needs to be further investigated. Author summary: Protection against tuberculosis (TB) requires a robust proinflammatory Th1-type immune response with cytokines like TNF and IFN-gamma being vital for cell recruitment and activation of microbicidal mechanisms, and granuloma formation to wall off the bacteria. Lately also the cytokine IL-17 was shown important for TB-protection. Helminths generally trigger a Th2-type immunity which suppresses Th1-type responses having consequences for TB reactivation and disease severity in endemic regions. To study helminths species-specific effects on the cytokine response for TB, which is not fully explored, we recruited patients with active pulmonary TB and healthy community controls (CCs) in Gondar, Ethiopia, and analyzed the Th1/Th2 cytokine profiles including IL-17A in plasma and from isolated and stimulated immune cells (PBMCs). In CCs confirmed not having latent TB we found that Ascaris lumbricoides or Schistosoma mansoni infection suppressed Th1 cytokines and IL-10 in PBMCs. In TB patients, on the other hand, only hookworm infection showed a similar pattern suppressing Th1 cytokines in PBMC, as well as suppressing the elevated systemic levels of IL-17A in plasma. Our findings show that helminths suppress the TB-protective cytokine output in a species-dependent manner whereby certain species possibly increase susceptibility to TB and others more strongly regulate immunity during TB disease. [ABSTRACT FROM AUTHOR]

Background: Clinical interpretation of trace results by Xpert MTB/RIF Ultra assay (Ultra) used as an initial diagnostic test for tuberculosis (TB) may be challenging. The aim of the study was to evaluate the frequency and epidemiology of trace readouts in routine clinical practice in a low TB prevalence setting and to propose guidance on how to manage patients with trace calls considering the data available (clinical, radiological, bacteriological etc.). Materials and methods: A retrospective, observational, monocentric study was conducted at IRCCS Azienda Ospedaliero-Universitaria of Bologna, Italy between November 2017—December 2020. Presumptive TB patients with at least one Ultra trace result during diagnostic workup before treatment were included in the study. Patients with ongoing anti-TB treatment at the time of the trace call result or with no clinical data available were excluded from the study. Results: Fifty-nine presumptive TB patients with Ultra trace readouts were included in the study (mean age 37.0 years, 61% males). Four patients had a history of TB in the last 2 years. Twenty-five (42.4%) of the 59 samples with trace results were respiratory material. 57/59 (96.6%) patients started anti-TB treatment soon after obtaining trace results, based on clinical, radiological or other information available, while for two patients with a recent history of TB the trace result did not lead to anti-TB treatment. Culture was positive for M. tuberculosis for 31/59 (52.5%) samples with trace calls: 13/25 (52.0%) were respiratory samples and 18/33 (54.5%) non-respiratory samples. The clinical and/or radiological findings of 47/57 (82.4%) patients given anti-TB therapy improved during treatment. Conclusion: In low TB incidence settings, Ultra trace calls in presumptive TB patients should be considered as true-positive and treatment should be started promptly, except in cases of recent history of TB, where careful evaluation of other diagnostic criteria is necessary before starting anti-TB treatment. A decisional algorithm for clinical management is proposed. [ABSTRACT FROM AUTHOR]

This paper investigates the determinants of COVID-19 infection in the first 100 days of government actions. Using a debiased LASSO estimator, we explore how different measures of government nonpharmaceutical interventions affect new infections of COVID-19 for 37 lower and middle-income countries (LMCs). We find that closing schools, stay-at-home restrictions, and contact tracing reduce the growth of new infections, as do economic support to households and the number of health care workers. Notably, we find no significant effects of business closures. Finally, infections become higher in countries with greater income inequality, higher tourist inflows, poorly educated adults, and weak governance quality. We conclude that several policy interventions reduce infection rates for poorer countries. Further, economic and institutional factors are important; thereby justifying the use, and ultimately success, of economic support to households during the initial infection period. [ABSTRACT FROM AUTHOR]

In Fall 2020, several European countries reported rapid increases in COVID-19 cases along with growing estimates of the effective reproduction rates. Such an acceleration in epidemic spread is usually attributed to time-dependent effects, e.g. human travel, seasonal behavioral changes, mutations of the pathogen etc. In this case however the acceleration occurred when counter measures such as testing and contact tracing exceeded their capacity limit. Considering Austria as an example, here we show that this dynamics can be captured by a time-independent, i.e. autonomous, compartmental model that incorporates these capacity limits. In this model, the epidemic acceleration coincides with the exhaustion of mitigation efforts, resulting in an increasing fraction of undetected cases that drive the effective reproduction rate progressively higher. We demonstrate that standard models which does not include this effect necessarily result in a systematic underestimation of the effective reproduction rate. [ABSTRACT FROM AUTHOR]

Background: Bluetooth-enabled smartphone apps have been developed and implemented in different sites globally to help overcome capacity limitations of traditional interview-based COVID-19 contact tracing. Two apps are currently available in Canada: ABTraceTogether exclusively in Alberta and COVID Alert in nine other provinces and territories. This study aims to examine factors associated with downloading of these apps to inform targeted promotion and marketing to increase app uptake. Methods: We performed a cross-sectional survey with adult participants (≥18 years old) from an online national panel. Participants were asked if they had downloaded an app and, if applicable, reasons for not downloading. Logistic regression was used to identify sociodemographic factors and trusted information sources associated with downloading and reasons for not downloading. Results: Of the included 4,503 respondents (36% response rate), 1,394 (31%) had downloaded an app. Demographic and socioeconomic factors positively associated with app download were: 1) being female, 2) higher household income, 3) higher education level attained, and 4) more liberal political views. The odds of downloading an app were higher for participants who trusted health-related information sources, and lower for those who trusted internet searches, family and friend, or Facebook. The most cited reasons for not downloading were related to data security concerns and perceived lack of benefit from the apps. Interpretation: These findings identify sociodemographic segments with the lowest app uptake, reasons for not downloading and trusted information sources to inform targeted promotion and marketing strategies to improve uptake of apps to facilitate contact tracing. [ABSTRACT FROM AUTHOR]

Background: India has experienced the second largest outbreak of COVID-19 globally, yet there is a paucity of studies analysing contact tracing data in the region which can optimise public health interventions (PHI's). Methods: We analysed contact tracing data from Karnataka, India between 9 March and 21 July 2020. We estimated metrics of transmission including the reproduction number (R), overdispersion (k), secondary attack rate (SAR), and serial interval. R and k were jointly estimated using a Bayesian Markov Chain Monte Carlo approach. We studied determinants of risk of further transmission and risk of being symptomatic using Poisson regression models. Findings: Up to 21 July 2020, we found 111 index cases that crossed the super-spreading threshold of ≥8 secondary cases. Among 956 confirmed traced cases, 8.7% of index cases had 14.4% of contacts but caused 80% of all secondary cases. Among 16715 contacts, overall SAR was 3.6% [95% CI, 3.4–3.9] and symptomatic cases were more infectious than asymptomatic cases (SAR 7.7% vs 2.0%; aRR 3.63 [3.04–4.34]). As compared to infectors aged 19–44 years, children were less infectious (aRR 0.21 [0.07–0.66] for 0–5 years and 0.47 [0.32–0.68] for 6–18 years). Infectors who were confirmed ≥4 days after symptom onset were associated with higher infectiousness (aRR 3.01 [2.11–4.31]). As compared to asymptomatic cases, symptomatic cases were 8.16 [3.29–20.24] times more likely to cause symptomatic infection in their secondary cases. Serial interval had a mean of 5.4 [4.4–6.4] days, and case fatality rate was 2.5% [2.4–2.7] which increased with age. Conclusion: We found significant heterogeneity in the individual-level transmissibility of SARS-CoV-2 which could not be explained by the degree of heterogeneity in the underlying number of contacts. To strengthen contact tracing in over-dispersed outbreaks, testing and tracing delays should be minimised and retrospective contact tracing should be implemented. Targeted measures to reduce potential superspreading events should be implemented. Interventions aimed at children might have a relatively small impact on reducing transmission owing to their low symptomaticity and infectivity. We propose that symptomatic cases could cause a snowballing effect on clinical severity and infectiousness across transmission generations; further studies are needed to confirm this finding. [ABSTRACT FROM AUTHOR]

Testing, contact tracing, and isolation (TTI) is an epidemic management and control approach that is difficult to implement at scale because it relies on manual tracing of contacts. Exposure notification apps have been developed to digitally scale up TTI by harnessing contact data obtained from mobile devices; however, exposure notification apps provide users only with limited binary information when they have been directly exposed to a known infection source. Here we demonstrate a scalable improvement to TTI and exposure notification apps that uses data assimilation (DA) on a contact network. Network DA exploits diverse sources of health data together with the proximity data from mobile devices that exposure notification apps rely upon. It provides users with continuously assessed individual risks of exposure and infection, which can form the basis for targeting individual contact interventions. Simulations of the early COVID-19 epidemic in New York City are used to establish proof-of-concept. In the simulations, network DA identifies up to a factor 2 more infections than contact tracing when both harness the same contact data and diagnostic test data. This remains true even when only a relatively small fraction of the population uses network DA. When a sufficiently large fraction of the population (≳ 75%) uses network DA and complies with individual contact interventions, targeting contact interventions with network DA reduces deaths by up to a factor 4 relative to TTI. Network DA can be implemented by expanding the computational backend of existing exposure notification apps, thus greatly enhancing their capabilities. Implemented at scale, it has the potential to precisely and effectively control future epidemics while minimizing economic disruption. Author summary: During the ongoing COVID-19 pandemic, exposure notification apps have been developed to scale up manual contact tracing. The apps use proximity data from mobile devices to automate notifying direct contacts of an infection source. The information they provide is limited because users receive only rare and binary alerts. Here we present network data assimilation (DA) as a new digital approach to epidemic management and control. Network DA uses the same data as exposure notification apps but uses it more effectively to provide frequently updated individual risk assessments to users. Network DA is based on automated learning about individuals' risk of exposure and infection from crowd-sourced health data and proximity data. The data are aggregated with models of disease transmission to produce statistical assessments of users' risks. In an extensive simulation study of the COVID-19 epidemic in New York City (NYC), we show that network DA with diagnostic testing achieves epidemic control with fewer than half the deaths that occurred during NYC's lockdown, while isolating a far smaller fraction of the population (typically only 5–10% of the population at any given time). Implemented at scale, then, network DA has the potential to effectively control epidemics while minimizing economic and social disruption. [ABSTRACT FROM AUTHOR]

The Covid19 pandemic has significantly impacted on our lives, triggering a strong reaction resulting in vaccines, more effective diagnoses and therapies, policies to contain the pandemic outbreak, to name but a few. A significant contribution to their success comes from the computer science and information technology communities, both in support to other disciplines and as the primary driver of solutions for, e.g., diagnostics, social distancing, and contact tracing. In this work, we surveyed the Italian computer science and engineering community initiatives against the Covid19 pandemic. The 128 responses thus collected document the response of such a community during the first pandemic wave in Italy (February-May 2020), through several initiatives carried out by both single researchers and research groups able to promptly react to Covid19, even remotely. The data obtained by the survey are here reported, discussed and further investigated by Natural Language Processing techniques, to generate semantic clusters based on embedding representations of the surveyed activity descriptions. The resulting clusters have been then used to extend an existing Covid19 taxonomy with the classification of related research activities in computer science and information technology areas, summarizing this work contribution through a reproducible survey-to-taxonomy methodology. [ABSTRACT FROM AUTHOR]