Asymptomatic Infected Individuals Research Articles

A mathematical model for transmission dynamics of COVID-19 infection.

In this paper, a mathematical model of COVID-19 has been proposed to study the transmission dynamics of infection by taking into account the role of symptomatic and asymptomatic infected individuals. The model has also considered the effect of non-pharmaceutical interventions (NPIs) in controlling the spread of virus. The basic reproduction number ( ) has been computed and the analysis shows that for , the disease-free state becomes globally stable. The conditions of existence and stability for two other equilibrium states have been obtained. Transcritical bifurcation occurs when basic reproduction number is one (i.e. ). It is found that when asymptomatic cases get increased, infection will persist in the population. However, when symptomatic cases get increased as compared to asymptomatic ones, the endemic state will become unstable and infection may eradicate from the population. Increasing NPIs decrease the basic reproduction number and hence, the epidemic can be controlled. As the COVID-19 transmission is subject to environmental fluctuations, the effect of white noise has been considered in the deterministic model. The stochastic differential equation model has been solved numerically by using the Euler-Maruyama method. The stochastic model gives large fluctuations around the respective deterministic solutions. The model has been fitted by using the COVID-19 data of three waves of India. A good match is obtained between the actual data and the predicted trajectories of the model in all three waves of COVID-19. The findings of this model may assist policymakers and healthcare professionals in implementing the most effective measures to prevent the transmission of COVID-19 in different settings.

A mathematical model for COVID-19 considering waning immunity, vaccination and control measures

In this work we define a modified SEIR model that accounts for the spread of infection during the latent period, infections from asymptomatic or pauci-symptomatic infected individuals, potential loss of acquired immunity, people’s increasing awareness of social distancing and the use of vaccination as well as non-pharmaceutical interventions like social confinement. We estimate model parameters in three different scenarios—in Italy, where there is a growing number of cases and re-emergence of the epidemic, in India, where there are significant number of cases post confinement period and in Victoria, Australia where a re-emergence has been controlled with severe social confinement program. Our result shows the benefit of long term confinement of 50% or above population and extensive testing. With respect to loss of acquired immunity, our model suggests higher impact for Italy. We also show that a reasonably effective vaccine with mass vaccination program are successful measures in significantly controlling the size of infected population. We show that for a country like India, a reduction in contact rate by 50% compared to a reduction of 10% reduces death from 0.0268 to 0.0141% of population. Similarly, for a country like Italy we show that reducing contact rate by half can reduce a potential peak infection of 15% population to less than 1.5% of population, and potential deaths from 0.48 to 0.04%. With respect to vaccination, we show that even a 75% efficient vaccine administered to 50% population can reduce the peak number of infected population by nearly 50% in Italy. Similarly, for India, a 0.056% of population would die without vaccination, while 93.75% efficient vaccine given to 30% population would bring this down to 0.036% of population, and 93.75% efficient vaccine given to 70% population would bring this down to 0.034%.

BACTERIAL INFECTION AND ANTIMICROBIAL SUSCEPTIBILITSY TEST (AST) PATTERNS AMONG CONFIRMED SARS COV-2 INDIVIDUAL IN SOUTHWESTERN NIGERIA.

Antimicrobial medications were given to patients with this illness without antimicrobial susceptibility since recent statistics on SARS-C0V-2 showed that bacterial infection increased mortality rate and lowered clearance rate of the virus. The goal of this study was to detect co-infecting pathogen(s) and analyze their antibiotic resistance profiles in confirmed SARS-CoV-2 cases in Oyo State, Nigeria. 400 symptomatic and asymptomatic infected individuals had their nasopharynx sampled, and structured questionnaires were given out to identify risk factors for SARS-CoV-2 infection. Using API 20E and VITEK 2.0 ID cards, isolates were recognized after being collected using conventional microbiological techniques. Antimicrobial susceptibility testing was done using VITEK 2.0 AST card kits and Kirby Bauer disc diffusion techniques. The Enterobacteriaceae family had a large number of the observed bacteria. The COVID-19 cases treated with azithromycin, which is more resistant to Gram positive bacteria, had a higher resistance rate (66.6%). However, bacterial isolates have significantly higher quinolone susceptibility (89.0%). Some of the microbiological isolates identified in individuals with SARS-CoV-2 infection were multidrug resistant, including Azithromycin. This discovery raises serious health concerns and requires additional investigation.

Genomic Epidemiology and Transmission Dynamics of Global Coxsackievirus B4.

The aim of this study was to determine the global genetic diversity and transmission dynamics of coxsackievirus B4 (CVB4) and to propose future directions for disease surveillance. Next-generation sequencing was performed to obtain the complete genome sequence of CVB4, and the genetic diversity and transmission dynamics of CVB4 worldwide were analyzed using bioinformatics methods such as phylogenetic analysis, evolutionary dynamics, and phylogeographic analysis. Forty complete genomes of CVB4 were identified from asymptomatic infected individuals and hand, foot, and mouth disease (HFMD) patients. Frequent recombination between CVB4 and EV-B multiple serotypes in the 3Dpol region was found and formed 12 recombinant patterns (A-L). Among these, the CVB4 isolated from asymptomatic infected persons and HFMD patients belonged to lineages H and I, respectively. Transmission dynamics analysis based on the VP1 region revealed that CVB4 epidemics in countries outside China were dominated by the D genotype, whereas the E genotype was dominant in China, and both genotypes evolved at a rate of > 6.50 × 10-3 substitutions/site/year. CVB4 spreads through the population unseen, with the risk of disease outbreaks persisting as susceptible individuals accumulate. Our findings add to publicly available CVB4 genomic sequence data and deepen our understanding of CVB4 molecular epidemiology.

Operational analysis for COVID-19 testing: Determining the risk from asymptomatic infections.

Testing remains a key tool for managing health care and making health policy during the coronavirus pandemic, and it will probably be important in future pandemics. Because of false negative and false positive tests, the observed fraction of positive tests-the surface positivity-is generally different from the fraction of infected individuals (the incidence rate of the disease). In this paper a previous method for translating surface positivity to a point estimate for incidence rate, then to an appropriate range of values for the incidence rate consistent with the model and data (the test range), and finally to the risk (the probability of including one infected individual) associated with groups of different sizes is illustrated. The method is then extended to include asymptomatic infections. To do so, the process of testing is modeled using both analysis and Monte Carlo simulation. Doing so shows that it is possible to determine point estimates for the fraction of infected and symptomatic individuals, the fraction of uninfected and symptomatic individuals, and the ratio of infected asymptomatic individuals to infected symptomatic individuals. Inclusion of symptom status generalizes the test range from an interval to a region in the plane determined by the incidence rate and the ratio of asymptomatic to symptomatic infections; likelihood methods can be used to determine the contour of the rest region. Points on this contour can be used to compute the risk (defined as the probability of including one asymptomatic infected individual) in groups of different sizes. These results have operational implications that include: positivity rate is not incidence rate; symptom status at testing can provide valuable information about asymptomatic infections; collecting information on time since putative virus exposure at testing is valuable for determining point estimates and test ranges; risk is a graded (rather than binary) function of group size; and because the information provided by testing becomes more accurate with more tests but at a decreasing rate, it is possible to over-test fixed spatial regions. The paper concludes with limitations of the method and directions for future work.

Modelling and analysis of the HIV/AIDS epidemic with fast and slow asymptomatic infections in China from 2008 to 2021.

The aim of this paper is to investigate the spread of the HIV/AIDS epidemic in China during 2008-2021. A new mathematical model is proposed to study the dynamics of HIV transmission with acute infection, fast asymptomatic infections, and slow asymptomatic infections. The basic reproduction number is obtained by the next-generation matrix method. A quantitative analysis of the model, including the local behavior, global behavior, and permanence, is performed. Numerical simulations are presented to enhance the results of these analyses. The behavior or the model's parameters are estimated from real data. A sensitivity analysis shows that the proportion of asymptomatic infections co-infected with other diseases significantly affects the basic reproduction number. We further analyze the impact of implementing single and multiple measure(s) in parallel with the epidemic. The study results conclude that multiple measures are more effective in controlling the spread of AIDS compared to just one. The HIV epidemic can be effectively curbed by reducing the contact rate between fast asymptomatic infected individuals and susceptible populations, increasing the early diagnosis and screening of HIV-infected individuals co-infected with other diseases, and treating co-infected patients promptly.

Dynamical models of acute respiratory illness caused by human adenovirus on campus

Acute respiratory illness caused by human adenovirus have been increasing in morbidity and mortality in recent years. Currently, isolation of symptomatic infected individuals is the primary means of controlling outbreaks in closed spaces such as schools and military camps. However, the disease is still spreading despite the implementation of control measures. To reveal the underlying mechanism of this phenomenon, we propose a dynamic model that considers invisible transmission and isolated confirmed cases. By calculating and analyzing the control reproduction number, it is found that asymptomatic infected individuals play an important role in the spread of the epidemic. Therefore, in the absence of specific vaccines, non-pharmaceutical interventions such as quarantine of exposed individuals are effective means to mitigate severity. The results show that the earlier the control of invisible transmission is implemented, the lower the peak and the shorter the duration of the outbreak. These findings will provide the theoretical basis and recommendations for prevention and control of human adenovirus transmission in closed spaces.

Sensitivity Analysis of SEIRS Model with Quarantine on the Spread of Covid-19

Since the Covid-19 pandemic, various mathematical models have been developed to describe its spread using the compartment model. The purpose of this research was to construct a new model of Covid-19. This formulated model is an application of SEIRS epidemic model by Zhang & Teng (2007) and a modification of the Covid-19 model by Chatterjee et al. (2020) by adding variations of quarantine. The model is analyzed by determining the disease-free fixed point and basic reproduction number 〖(R〗_0) through the next generation matrix method. The next step is to analyze the sensitivity to find out the parameters that have the most influence on the spread of Covid-19. The disease will not spread in the population if the value of R_0<1, while the disease will spread if the value of R_0>1. The result of the sensitivity analysis stated the parameters that can be controlled and have the most significant effect, respectively, are the transmission rate from symptomatic infected individuals (β_2 ),transmission rates from asymptomatic infected individuals (β_1 ), quarantine rates for symptomatic infected individuals (θ_3), and quarantine rates for asymptomatic infected individuals (θ_2). Parameters β_2 and β_1 have a negative index, while θ_3 and θ_2 have a negative index. It means decreasing the transmission rate from infected individuals and increasing the quarantine rate for infected individuals can decrease the spread of Covid-19. Therefore there will not be an outbreak in the long term.

Nonlinear dynamics of an epidemic compartment model with asymptomatic infections and mitigation

A significant proportion of the infections driving the current SARS-CoV-2 pandemic are transmitted asymptomatically. Here we introduce and study a simple epidemic model with separate compartments comprising asymptomatic and symptomatic infected individuals. The linear dynamics determining the outbreak condition of the model is equivalent to a renewal theory approach with exponential waiting time distributions. Exploiting a nontrivial conservation law of the full nonlinear dynamics, we derive analytic bounds on the peak number of infections in the absence and presence of mitigation through isolation and testing. The bounds are compared to numerical solutions of the differential equations.

Low sensitivity of the COVID-19 antigen test (PANBIO™ COVID-19 Ag rapid test) to detect asymptomatic infections in health personnel of the National Institute of Respiratory Diseases.

BackgroundCOVID-19 requires an early diagnosis to optimize management and limit transmission. SARS-CoV-2 is able to spread effectively. Infected asymptomatic individuals have been found to be contagious. RT-qPCR is the currently recommended laboratory method for diagnosing acute infection. However, rapid antigen detection (RAD) tests are not only fast, but require less specialized training. The possibility of using RAD tests to identify asymptomatic patients is attractive, as it could effectively contribute to minimizing the hospital spread of SARS-CoV-2. The objective of the study was to determine the performance of RAD vs. RT-qPCR for the detection of asymptomatic cases in INER health personnel.MethodsIn order to follow WHO guidelines, generalized tests, a test station for health care workers was implemented on demand. A rapid test was carried out and a second sample was taken to be processed by RT-qPCR. With the results of both tests we conducted a retrospective study. Sensitivity, specificity, positive predictive value, negative predictive value and negative likelihood ratios were calculated.ResultsA total of 1640 RAD tests were performed in health care workers (mean age was 39, 69, 47% with a self-reported comorbidity). Participants provided 1,640 valid RAD/RT-qPCR test pairs with 2% testing positive via RT-qPCR. 12 RAD samples were positive for SARS-CoV-2. Overall sensitivity of the PANBIO ™ COVID-19 Ag Rapid Test test was 35.2%.ConclusionsRADs are not recommended for the detection of asymptomatic cases due to low performance.

Transmission dynamics of disease spreading in multilayer networks with mass media.

On the basis of existing disease spreading research, in this paper we propose a Hesitant-Taken-Unaware-Aware-Susceptible-Asymptomatic-Symptomatic-Recovered (HTUA-SI^{a}I^{s}R) model with mass media in a two-layer network, which consists of a virtual communication layer and a physical contact layer. Based on the UAU-SIR model, we additionally consider three practical factors, including whether individuals will disseminate information or not, the influence of unaware individuals on aware individuals, and the direct recovery of asymptomatic infected individuals. Based on the microscopic Markov chain approach (MMCA), for the proposed HTUA-SI^{a}I^{s}R model, MMCA equationsare generated and the analytical expression of the epidemic threshold is obtained. Compared with Monte Carlo techniques, numerical simulations show the feasibility and effectiveness of the MMCA equations, as well as the HTUA-SI^{a}I^{s}R model theoretically. Meanwhile, extensive simulations demonstrate that the acceleration of the awareness dissemination in the virtual communication layer can effectively block the epidemic spreading and raise the epidemic threshold. However, under certain conditions, the increasing of T-state individuals will increase the U-state individuals because the T-state and U-state individuals can influence the A-state individuals losing their awareness of protection, and then promote the epidemic spreading and decrease the epidemic threshold. In addition, reducing asymptomatic infections can hinder the epidemic spreading. But, when the recovery rate of asymptomatic infections is greater than that of symptomatic infections, decreasing the tendency of individuals acquiring asymptomatic infections will lower the epidemic threshold.

How many asymptomatic cases were unconfirmed in the US COVID-19 pandemic? The evidence from a serological survey

A serological survey from CDC revealed more than 10% of individuals in America probably resolving or past infection with SARS-CoV-2 at the end of 2020, which illustrated there were massive unconfirmed asymptomatic infected people by contrast with the reported cases numbers. Asymptomatic patients as one of the crucial reasons for the COVID-19 pandemic being tough to contain, estimating the number of unconfirmed ones including the active infected and having cured in this population, is of great guiding significance for formulating epidemic prevention and control policies. This paper proposes a varying coefficient Susceptible–Infected–Removed–Susceptible (vSIRS) model to obtain the time series data of the unconfirmed asymptomatic infected numbers. Moreover, due to the time-varying coefficients, we can effectively track the situation changes of the COVID-19 intervened by related policy support and medical care level through this epidemiological model. A novel two-stage approach with a programming problem is correspondingly developed to accomplish the estimation of the unknown parameters in the vSIRS model. Subsequently, by leveraging seroprevalence data, daily reported cases data, and other clinical information, we apply the vSIRS model to analyze the evolution of COVID-19 in America. The modeling results show millions of active asymptomatic infected individuals were unconfirmed during the autumn and winter of 2020, which was a momentous factor for driving American COVID-19 pandemic.

Modeling and Analysis of COVID-19 Spread: The Impacts of Nonpharmaceutical Protocols.

In this study, the extended SEIR dynamical model is formulated to investigate the spread of coronavirus disease (COVID-19) via a special focus on contact with asymptomatic and self-isolated infected individuals. Furthermore, a mathematical analysis of the model, including positivity, boundedness, and local and global stability of the disease-free and endemic equilibrium points in terms of the basic reproduction number, is presented. The sensitivity analysis indicates that reducing the disease contact rate and the transmissibility factor related to asymptomatic individuals, along with increasing the quarantine/self-isolation rate and the contact-tracing process, from the view of flattening the curve for novel coronavirus, are crucial to the reduction in disease-related deaths.

Anti-folate quintuple mutations in Plasmodium falciparum asymptomatic infections in Yaoundé, Cameroon

A major challenge in the fight to effectively control malaria is the emergence of resistant parasite to drugs used in therapy as well as for chemoprevention. In this study, single nucleotide polymorphisms (SNPs) associated with Plasmodium falciparum resistance to sulfadoxine-pyrimethamine (SP), one of the partner drugs in artemisinin-based therapies (ACTs) were studied in asymptomatic P. falciparum isolates from Cameroon. Dried Blood spots were collected from children with asymptomatic malaria enrolled during a household survey. The P. falciparum dihydrofolate reductase (Pfdhfr), dihydropteroate synthase (Pfdhps) and Kelch 13 genes were amplified and point mutations in these gene sequences were analyzed by sequencing. Among a total of 234 samples collected, 51 showed parasitaemia after microscopic examination of which 47 were P. falciparum mono-infections. Molecular analysis revealed 97.3% of mutant alleles at codons 51I, 59R and 108 N in Pfdhfr gene. In Pfdhps gene the most common mutation was 437G (83.3%); followed by 436A (47.6%) and 436F (28.6%). The association of mutations in the two genes (dhfr + dhps) showed 11 different haplotypes including three sextuple mutants (IRNI + AGKGA, IRNI + AAKGS, IRNI + AGKAS) and one septuple mutant (IRNI + AGKGS). For K13 gene no SNPs were seen in the studied asymptomatic malaria samples. The findings revealed presence of SP-resistant alleles in asymptomatic infected individuals with presence of sextuples and septuple SNPs. This emphasizes that regular profiling of antimalarial drugs resistance markers in such population is essential for malaria control and elimination programmes.

Mathematical modeling for COVID-19 with focus on intervention strategies and cost-effectiveness analysis.

The realistic assessments of public health intervention strategies are of great significance to effectively combat the COVID-19 epidemic and the formation of intervention policy. In this paper, an extended COVID-19 epidemic model is devised to assess the severity of the pandemic and explore effective control strategies. The model is characterized by ordinary differential equations with seven-state variables, and it incorporates some parameters associated with the interventions (i.e., media publicity, home isolation, vaccination and face-mask wearing) to investigate the impacts of these interventions on the spread of the COVID-19 epidemic. Some dynamic behaviors of the model, such as forward and backward bifurcation, are analyzed. Specifically, we calibrate the model parameters using actual COVID-19 infected data in Brazil by Markov Chain Monte Carlo algorithm such that we can study the effects of interventions on a practical case. Through a comprehensive exploration of model design and analysis, model calibration, sensitivity analysis, implementation of optimal control problems and cost-effectiveness analysis, the rationality of our model is verified, and the effective strategies to combat the epidemic in Brazil are revealed. The results show that the asymptomatic infected individuals are the main drivers of COVID-19 transmission, and rapid detection of asymptomatic infections is critical to combat the COVID-19 epidemic in Brazil. Interestingly, the effect of the vaccination rate associated with pharmaceutical intervention on the basic reproduction number is much lower than that of non-pharmaceutical interventions (NPIs). Our study also highlights the importance of media publicity. To reduce the infected individuals, the multi-pronged NPIs have considerable positive effects on controlling the outbreak of COVID-19. The infections are significantly decreased by the early implementation of media publicity complemented with home isolation and face-mask wearing strategy. When the cost of implementation is taken into account, the early implementation of media publicity complemented with a face-mask wearing strategy can significantly mitigate the second wave of the epidemic in Brazil. These results provide some management implications for controlling COVID-19.

Protective Effect of Inactivated COVID-19 Vaccines against Progression of SARS-CoV-2 Omicron and Delta Variant Infections to Pneumonia in Beijing, China, in 2022.

This real-world study explores the effect of coronavirus disease 2019 (COVID-19) inactivated vaccines on the prevention of asymptomatic or mild Delta or Omicron variant infections progressing to pneumonia. Association between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia cases and vaccination was measured with a multivariable logistic regression, stratified by genotype and age groups. We recruited 265 cases (111 (41.9%) infected with Delta and 154 (58.1%) with Omicron variants). There were 22 asymptomatic infected individuals, 156 mild cases without pneumonia, and 87 moderate cases with pneumonia. There was a markedly increased risk of progression to pneumonia in Delta infected cases, unvaccinated, or partially vaccinated COVID-19 patients with diabetes and those aged ≥60 years. Patients who had completed booster doses of inactivated vaccines had a reduced risk of 81.6% (95% CI: 55.6–92.4%) in progressing to pneumonia over those who were unvaccinated or partially vaccinated. The risk of progressing to pneumonia was less reduced by 88.7% (95% CI: 56.6–97%) and 73.9% (95% CI: 1.4–93.1%) among Delta and Omicron-infected patients, and was reduced by 78.5% (95% CI: 45.3–91.6%) and 94.1% (95% CI: 21.5–99.6%) among patients aged <60 and ≥60 years, respectively. Our data indicated that a complete vaccination with a booster reduced the risk of asymptomatic or mild Delta or Omicron variant COVID-19 progressing to pneumonia and, thus, reduced the pressure of severe illness on medical resources.

The Road to HTLV-1-Induced Leukemia by Following the Subcellular Localization of HTLV-1-Encoded HBZ Protein.

Human T cell leukemia virus-1 (HTLV-1) is the causative agent of a severe cancer of the lymphoid lineage that develops in 3-5% of infected individuals after many years. HTLV-1 infection may also induce a serious inflammatory pathology of the nervous system designated HTLV-associated myelopathy/tropical spastic paraparesis (HAM/TSP). Two virus-encoded proteins, the viral transactivator Tax-1 and the HTLV-1 basic leucine-zipper factor HBZ, are strongly involved in the oncogenic process. Tax-1 is involved in initial phases of the oncogenic process. Conversely, HBZ seems to be involved in maintenance of the neoplastic state as witnessed by the generation of leukemic/lymphomatous phenotype in HBZ transgenic mice and the persistent expression of HBZ in all phases of the oncogenic process. Nevertheless, the intimate molecular and cellular mechanism mediated by the two viral proteins, particularly HBZ, in oncogenesis still remain elusive. An important step toward the complete comprehension of HBZ-associated oncogenicity is the clarification of the anatomical correlates of HBZ during the various phases of HTLV-1 infection to development of HTLV-1-associated inflammatory pathology and ultimately to the establishment of leukemia. In this review, I will summarize recent studies that have established for the first time a temporal and unidirectional expression of HBZ, beginning with an exclusive cytoplasmic localization in infected asymptomatic individuals and in HAM/TSP patients and ending to a progressive cytoplasmic-to-nuclear transition in leukemic cells. These results are framed within the present knowledge of HTLV-1 infection and the future lines of research that may shed new light on the complex mechanism of HTLV-1- mediated oncogenesis.

Wastewater based epidemiology as a silent sentinel of the trend of SARS-CoV-2 circulation in the community in central Argentina

Monitoring wastewater for the traces of viruses allows effective surveillance of entire communities, including symptomatic and asymptomatic infected individuals, providing information on whether a specific pathogen is circulating in a population. In the context of the COVID-19 pandemic, 261 wastewater samples from six communities of the province of Córdoba, Argentina were analyzed. From mid-May 2020 to the end of August 2021, raw sewage samples were collected from the central network pipe that enters into the Wastewater Treatment Plants (WWTP) in Córdoba city and five communities in the Punilla Valley. SARS-CoV-2 was concentrated by using the polyethylene glycol-6000 precipitation method. Viral genomes were extracted from concentrated samples, and N- and E-SARS-CoV-2 genes were detected by using real time RT-PCR. Wastewater samples that resulted positive for SARS-CoV-2 genome detection were subjected to viral variants of concern (VOCs) identification by real time RT-PCR. Overall, just by using the identification of the N gene or E gene, the rates of viral genome detection were 43.4% (86/198) and 51.5% (102/198) respectively, and by using both methodologies (positivity criterion: detection of N and / or E gene), the detection rate was 71.2% (141/198). Thereby, the optimal strategy to study the SARS-CoV-2 genome in wastewater would be the use of the combined detection of both genes. Detection of SARS-CoV-2 variants in wastewater reflected their circulation in the community, showing no VOCs detection in the first COVID-19 wave and their co-circulation with Gamma, Alpha and Delta VOCs during 2021. Therefore, SARS-CoV-2 Wastewater Based Epidemiology (WBE) described the introduction, permanence and/or the co-circulation of viral variants in the community. In geographical areas with a stable population, SARS-CoV-2 WBE could be used as an early warning sign of new COVID-19 cases, whereas in localities with a low number of inhabitants and high tourist influx, WBE may only be useful to reflect the circulation of the virus in the community. Overall, the monitoring of SARS-CoV-2 in wastewater can become a silent sentinel of the trend of viral circulation in the community, providing supplementary information for clinical surveillance to support public health measures.

Sideward contact tracing and the control of epidemics in large gatherings.

Effective contact tracing is crucial to containing epidemic spreading without disrupting societal activities, especially during a pandemic. Large gatherings play a key role, potentially favouring superspreading events. However, the effects of tracing in large groups have not been fully assessed so far. We show that in addition to forward tracing, which reconstructs to whom the disease spreads, and backward tracing, which searches from whom the disease spreads, a third 'sideward' tracing is always present, when tracing gatherings. This is an indirect tracing that detects infected asymptomatic individuals, even if they have been neither directly infected by nor directly transmitted the infection to the index case. We analyse this effect in a model of epidemic spreading for SARS-CoV-2, within the framework of simplicial activity-driven temporal networks. We determine the contribution of the three tracing mechanisms to the suppression of epidemic spreading, showing that sideward tracing induces a non-monotonic behaviour in the tracing efficiency, as a function of the size of the gatherings. Based on our results, we suggest an optimal choice for the sizes of the gatherings to be traced and we test the strategy on an empirical dataset of gatherings on a university campus.

Free PoC Testing for SARS-CoV-2 in Germany: Factors Expanding Access to Various Communities in a Medium-Sized City.

During the third wave of the COVID-19 (coronavirus disease 2019) pandemic in Germany, free SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) point-of-care (PoC) antigen tests were offered to citizens at least once a week to prevent spreading by asymptomatic infected individuals. This study investigated user groups, timing, frequency, and test center locations in a typical medium-sized European city. We analyzed 27,369 pseudonymized datasets from eight centers over 12 weeks. Those were evaluated according to age, residence, appointment, and potential repeated test occurrence. The centers were visited by different groups; some centers were preferred by a predominantly younger demographic, whereas a mobile option attracted an older age group by reaching districts with few other testing possibilities. Elderly individuals were tested more spontaneously than younger individuals, and a test center at a ‘park and ride’ had more spontaneous visitors from outside of the city compared to other test locations. Only a small proportion of less than 4% came for testing more than five times. To preferably address many people for voluntary antigen testing, it is crucial to offer different test opportunities accounting for individual behavioral patterns, despite this requiring more complex and costly design than conventional forms.