Infectious Transmission Model Research Articles

Government Subsidies and Policies for Mask Production Under COVID-19: Is It Wise to Control Less?

Under the COVID-19 pandemic, governments worldwide have subsidized manufacturers or consumers on the production or purchase of masks. However, the impacts of these subsidies on the mask supply chain (MSC) operations are unclear. Motivated by our interview with a mask manufacturer as well as the observed real-world practices, we establish consumer utility-based stylized models to analytically examine government subsidies and policies in the MSC. We utilize the infection transmission model to capture the social health risk during the COVID-19 outbreak. The government aims to maximize social welfare, which includes the manufacturer's profit, consumer surplus, social health risk, and government subsidy expenditure. Results indicate that when the price is not controlled (i.e., the manufacturer decides it), the manufacturer and consumer subsidy programs are equally efficient in enhancing consumer surplus as well as reducing harm to social health risk under COVID-19. Thus, the government can conduct a subsidy scheme that is easier to implement in practice. However, we surprisingly find that the government's excessive intervention will cause disequilibrium in the MSC. When the price or the manufacturer's dishonest behavior is fully controlled by the government, subsidizing the MSC is not always advisable. Besides, our findings are consistent with the public interest theory; that is, the proper implementation of dishonesty prevention and pricing control policies can improve social welfare but sacrifice consumer surplus. Our results contribute to healthcare operations management and generate managerial insights for MSC management during COVID-19 with industrial validation.

A competitive infectious transmission model

Compartmental disease transmission models are widely used to model state transmission in infectious diseases, using differential equations to model the change in the number of units in different states over time, and recently has produced significant practical implications in many downstream fields. However, inspired by the transmission of rumors in social media, we note that the previous compartmental transfer models neglect the "competitiveness" during the transfer process, that is, the "infection" of people with positive and negative opinions to "susceptibles" or even people with opposing views. To tackle the above issues, in this paper, we propose a novel competitive infectious transmission model in which the "infection" will lead to more people supporting the opinion of the infector, effectively establishing the change of the number of units in the positive, negative, and neutral parties over time. In addition, we performed extensive theoretical analysis to investigate the property of the disease-free equilibrium and to calculate the basic reproduction numbers for three different scenarios. For each system, we derive explicit solutions for the basic reproduction numbers and discuss their important implications for guidance in practice.

Evaluation of three hemagglutinin-based vaccines for the experimental control of a panzootic clade 2.3.4.4b A(H5N8) high pathogenicity avian influenza virus in mule ducks

In France during winter 2016–2017, 487 outbreaks of clade 2.3.4.4b H5N8 subtype high pathogenicity (HP) avian influenza A virus (AIV) infections were detected in poultry and captive birds. During this epizootic, HPAIV A/decoy duck/France/161105a/2016 (H5N8) was isolated and characterized in an experimental infection transmission model in conventional mule ducks. To investigate options to possibly protect such ducks against this HPAIV, three vaccines were evaluated in controlled conditions. The first experimental vaccine was derived from the hemagglutinin gene of another clade 2.3.4.4b A(H5N8) HPAIV. It was injected at three weeks of age, either alone (Vac1) or after a primer injection at day-old (Vac1 + boost). The second vaccine (Vac2) was a commercial bivalent adjuvanted vaccine containing an expressed hemagglutinin modified from a clade 2.3.2 A(H5N1) HPAIV. Vac2 was administered as a single injection at two weeks of age. The third experimental vaccine (Vac3) also incorporated a homologous 2.3.4.4b H5 HA gene and was administered as a single injection at three weeks of age. Ducks were challenged with HPAIV A/decoy duck/France/161105a/2016 (H5N8) at six weeks of age. Post-challenge virus excretion was monitored in vaccinated and control birds every 2–3 days for two weeks using real-time reverse-transcription polymerase chain reaction and serological analyses (haemagglutination inhibition test against H5N8, H5 ELISA and AIV ELISA) were performed. Vac1 abolished oropharyngeal and cloacal shedding to almost undetectable levels, whereas Vac3 abolished cloacal shedding only (while partially reducing respiratory shedding) and Vac2 only partly reduced the respiratory and intestinal excretion of the challenge virus. These results provided relevant insights in the immunogenicity of recombinant H5 vaccines in mule ducks, a rarely investigated hybrid between Pekin and Muscovy duck species that has played a critical role in the recent H5 HPAI epizootics in France.

Virus transmission risk of college students in railway station during Post-COVID-19 era: Combining the social force model and the virus transmission model

In the post-epidemic era, people’s lives are gradually returning to normal, and travel is gradually resuming. The safe evacuation of cross-regional travelers in railway station has also attracted more and more attention, especially the evacuation behavior of college students in railway station. In this paper, considering the pedestrian dynamics mechanism in the emergency evacuation process during the COVID-19 normalized epidemic prevention and control, an Agent-based social force model was established to simulate the activities of college students in railway station. Combined with the virus infection transmission model, Monte Carlo simulation was used to calculate the total exposure time and the number of high-risk exposed people in the railway station evacuation process. In addition, sensitivity analysis was conducted on the total exposure time and the number of high-risk exposed people under 180 combinations of the number of initial infections, social distance, and the proportion of people wearing masks incorrectly. The results show that with the increase of social distances, the total exposure time and the number of high-risk exposures do not always decrease, but increase in some cases. The presence or absence of obstacles in the evacuation scene has no significant difference in the effects on total exposure time and the number of high-risk exposures. During the evacuation behavior of college students in railway station, choosing the appropriate number of lines can effectively reduce the total exposure time and the number of high-risk exposures. Finally, some policy suggestions are proposed to reduce the risk of virus transmission in the railway station evacuation process, such as choosing dynamic and reasonable social distance and the number of queues, and reducing obstacles.

A mesoscale agent based modeling framework for flow-mediated infection transmission in indoor occupied spaces

The ongoing Covid-19 pandemic, and its associated public health and socioeconomic burden, has reaffirmed the necessity for a comprehensive understanding of flow-mediated infection transmission in occupied indoor spaces. This is an inherently multiscale problem, and suitable investigation approaches that can enable evidence-based decision-making for infection control strategies, interventions, and policies; will need to account for flow physics, and occupant behavior. Here, we present a mesoscale infection transmission model for human occupied indoor spaces, by integrating an agent-based human interaction model with a flow physics model for respiratory droplet dynamics and transport. We outline the mathematical and algorithmic details of the modeling framework, and demonstrate its validity using two simple simulation scenarios that verify each of the major sub-models. We then present a detailed case-study of infection transmission in a model indoor space with 60 human occupants; using a systematic set of simulations representing various flow scenarios. Data from the simulations illustrate the utility and efficacy of the devised mesoscale model in resolving flow-mediated infection transmission; and elucidate key trends in infection transmission dynamics amongst the human occupants.

An agent-based study on the airborne transmission risk of infectious disease in a fever clinic during COVID-19 pandemic

Prevention of nosocomial infections is particularly important for the control of COVID-19 pandemic. We conducted a field study and performed extensive numerical simulations of infection transmission in a fever clinic during pandemic through an agent-based model with pedestrian dynamic and an infection transmission model. Furthermore, we evaluated the cross-infection risk of the patients influenced by the patient inject flow, medical service capability and plane layout. The service capability of fever clinic is determined by the least efficient medical session. When patient inject flow exceeded the service capability, the average dwell time, contact time, exposure dose, and risk of infection of patients all increased dramatically. With the patient inject flow exceeding the service capability, the growth rate of the contact time between patients and the cross-infection risk increased by 11.5-fold and 29.5-fold, respectively. The plane layout of the fever clinic affected the exposure dose and risk of infection. The waiting areas in the fever clinic had the highest risk, where the cumulative exposure dose of virus occupied up to 66.5% of the total. Our research will help to evaluate the biosafety of hospital buildings used for the diagnosis and treatment of infectious diseases.

COVID-19: Risk Analysis in South Asia with Respect to Europe and North America

Coronavirus Disease 2019 (COVID-19) was identified in late 2019 and world health Organization (WHO) declared as a pandemic on March 11, 2019. World top researchers, physician and pharmacists are trying to find out remedy but it is still in research phase. COVID-19 spread through the air by coughing or sneezing also depends on environment. In this paper, our main goal is to COVID-19 threat analysis in South Asian people based on their habits, culture, consciousness etc. compare to Europe and North American culture. The research work is formulated in three steps. First, we formulate a dynamic infection transmission model by considering the fertility rate, mortality rate, transmission rate, and cure rate of the COVD-19 caused death rate as variables. Second, we define the variables of the model based on the census of south Asia. Finally, we analyze the threat that COVID-19 can cause to the population of crowded country likes Bangladesh, India etc. in south Asia.

How risky is it to visit a supermarket during the pandemic?

We performed large-scale numerical simulations using a composite model to investigate the infection spread in a supermarket during a pandemic. The model is composed of the social force, purchasing strategy and infection transmission models. Specifically, we quantified the infection risk for customers while in a supermarket that depended on the number of customers, the purchase strategies and the physical layout of the supermarket. The ratio of new infections compared to sales efficiency (earned profit for customer purchases) was computed as a factor of customer density and social distance. Our results indicate that the social distance between customers is the primary factor influencing infection rate. Supermarket layout and purchasing strategy do not impact social distance and hence the spread of infection. Moreover, we found only a weak dependence of sales efficiency and customer density. We believe that our study will help to establish scientifically-based safety rules that will reduce the social price of supermarket business.

A Randomized Clinical Trial to Compare Plasmodium falciparum Gametocytemia and Infectivity After Blood-Stage or Mosquito Bite-Induced Controlled Malaria Infection.

BackgroundFor malaria elimination efforts, it is important to better understand parasite transmission to mosquitoes and develop models for early-clinical evaluation of transmission-blocking interventions.MethodsIn a randomized open-label trial, 24 participants were infected by bites from Plasmodium falciparum 3D7-infected mosquitoes (mosquito bite [MB]; n = 12) or by induced blood-stage malaria (IBSM) with the same parasite line (n = 12). After subcurative piperaquine treatment, asexual parasite and gametocytes kinetics were assessed, and mosquito feeding experiments were performed.ResultsStudy procedures were well tolerated. The median peak gametocyte density was 1304/mL (interquartile range, 308–1607/mL) after IBSM, compared with 14/mL (10–64/mL) after MB inoculation (P < .001), despite similar peak asexual parasite densities (P = .48). Peak gametocyte density was correlated with preceding pfap2-g transcripts, indicative of gametocyte commitment (ρ = 0.62; P = .002). Direct feeding assays resulted in mosquito infections from 9 of 12 participants after IBSM versus 0 of 12 after MB inoculation (P < .001).ConclusionsWe observed a striking effect of inoculation method on gametocyte production, suggesting higher gametocyte commitment after IBSM. Our direct comparison of MB and IBSM establishes the controlled human malaria infection transmission model, using intravenous administration of P. falciparum–infected erythrocytes as a model for early-clinical evaluation of interventions that aim to interrupt malaria transmission.Clinical Trial RegistrationNCT03454048

Controlled Human Malaria Infection Transmission Model - Phase A

Controlled Human Malaria Infection Transmission Model - Phase A

Reactive school closure weakens the network of social interactions and reduces the spread of influenza

School-closure policies are considered one of the most promising nonpharmaceutical interventions for mitigating seasonal and pandemic influenza. However, their effectiveness is still debated, primarily due to the lack of empirical evidence about the behavior of the population during the implementation of the policy. Over the course of the 2015 to 2016 influenza season in Russia, we performed a diary-based contact survey to estimate the patterns of social interactions before and during the implementation of reactive school-closure strategies. We develop an innovative hybrid survey-modeling framework to estimate the time-varying network of human social interactions. By integrating this network with an infection transmission model, we reduce the uncertainty surrounding the impact of school-closure policies in mitigating the spread of influenza. When the school-closure policy is in place, we measure a significant reduction in the number of contacts made by students (14.2 vs. 6.5 contacts per day) and workers (11.2 vs. 8.7 contacts per day). This reduction is not offset by the measured increase in the number of contacts between students and nonhousehold relatives. Model simulations suggest that gradual reactive school-closure policies based on monitoring student absenteeism rates are capable of mitigating influenza spread. We estimate that without the implemented reactive strategies the attack rate of the 2015 to 2016 influenza season would have been 33% larger. Our study sheds light on the social mixing patterns of the population during the implementation of reactive school closures and provides key instruments for future cost-effectiveness analyses of school-closure policies.

Determinants of Short-term Movement in a Developing Region and Implications for Disease Transmission.

Human mobility is important for infectious disease spread. However, little is known about how travel varies by demographic groups and how this heterogeneity influences infectious disease risk. We analyzed 10 years of survey data from 15 communities in a remote but rapidly changing region in rural Ecuador where road development in the past 15-20 years has dramatically changed travel. We identify determinants of travel and incorporate them into an infection transmission model. Individuals living in communities more remote at baseline had lower travel rates compared with less remote villages (adjusted odds ratio [OR] = 0.51; 95% confidence interval [CI] = 0.38, 0.67). Our model predicts that less remote villages are, therefore, at increased disease risk. Though road building and travel increased for all communities, this risk differential remained over 10 years of observation. Our transmission model also suggests that travelers and nontravelers have different roles in disease transmission. Adults travel more than children (adjusted OR = 1.73; 95% CI = 1.30, 2.31) and therefore disseminate infection from population centers to rural communities. Children are more likely than adults to be infected locally (attributable fraction = 0.24 and 0.09, respectively) and were indirectly affected by adult travel patterns. These results reinforce the importance of large population centers for regional transmission and show that children and adults may play different roles in disease spread. Changing transportation infrastructure and subsequent economic and social transitions are occurring worldwide, potentially causing increased regional risk of disease.

Quantification of the horizontal transmission of Mycoplasma synoviae in non-vaccinated and MS-H-vaccinated layers

ABSTRACTThe number of newly infected birds attributable to one infectious bird per day (= transmission rate β) was assessed in non-vaccinated and MS-H-vaccinated experimental specified pathogen-free White Leghorns after Mycoplasma synoviae challenge. Furthermore, the effect of vaccination on the shedding of the challenge strain was determined. The following groups were made: a negative control group (n = 5), a vaccinated (MS-H vaccine by eye drop (>105.7 colour changing units/bird)) non-challenged group (n = 5), two non-vaccinated challenged groups (n = 18 each) and two vaccinated challenged groups (n = 18 each). In the challenged groups, six seeder birds were intratracheally inoculated with 105.4 colony forming units (CFUs)/bird. Trachea swabs were taken at day (D)2, D3, D4, D5, D7, D9, D11, D14, D17, D21, D25, D28, D32, D35, D42 and D46 after contact with seeders and analyzed with a quantitative PCR able to detect the vaccine and field strain separately. The transmission rate and shedding were estimated using the susceptible exposed infectious transmission model and a linear mixed model, respectively. The mean shedding of the challenge strain was 106.4 CFU equivalents M. synoviae/g trachea mucus in vaccinates shedding MS-H, while in the birds not shedding the vaccine (non-vaccinates and vaccinates not shedding MS-H) it was 106.9 CFU equivalents M. synoviae/g trachea mucus. In vaccinates shedding MS-H, β was 0.0012 (95% C.I.: 0.00048 – 0.0024), while in birds not shedding vaccine (non-vaccinates and vaccinates not shedding MS-H) a significantly higher β of 0.022 (95% C.I.: 0.015 – 0.031) was found.

Mechanisms of hypervirulent Clostridium difficile ribotype 027 displacement of endemic strains: an epidemiological model.

Following rapid, global clonal dominance of hypervirulent ribotypes, Clostridium difficile now constitutes the primary infectious cause of nosocomial diarrhoea. Evidence indicates at least three possible mechanisms of hypervirulence that facilitates the successful invasion of these atypical strains: 1) increased infectiousness relative to endemic strains; 2) increased symptomatic disease rate relative to endemic strains; and 3) an ability to outcompete endemic strains in the host’s gut. Stochastic simulations of an infection transmission model demonstrate clear differences between the invasion potentials of C. difficile strains utilising the alternative hypervirulence mechanisms, and provide new evidence that favours certain mechanisms (1 and 2) more than others (3). Additionally, simulations illustrate that direct competition between strains (inside the host’s gut) is not a prerequisite for the sudden switching that has been observed in prevailing ribotypes; previously dominant C. difficile strains can be excluded by hypervirulent ribotypes through indirect (exploitative) competition.

The Allee effect and elimination of neglected tropical diseases: a mathematical modelling study.

Elimination and control programmes for neglected tropical diseases (NTDs) are underway around the world, yet they are generally informed by epidemiological modelling only to a rudimentary degree. Chief among the modelling-derived predictors of disease emergence or controllability is the basic reproduction number R0. The ecological systems of several of the NTDs include density-dependent processes--which alter the rate of e.g. parasite establishment or fecundity--that complicate the calculation of R0. Here we show how the forms of the density-dependent functions for a model of the NTD lymphatic filariasis affect the effective reproduction number Reff. We construct infection transmission models containing various density-dependent functions and show how they alter the shape of the Reff profile, affecting two important epidemiological outcome variables that relate to elimination and control programmes: the parasite transmission breakpoint (or extinction threshold) and the reproduction fitness, as measured by Reff. The current drive to control, eliminate or eradicate several parasitic infections would be substantially aided by the existence of ecological Allee effects. For these control programmes, the findings of this paper are encouraging, since a single positive density dependency (DD) can introduce a reasonable chance of achieving elimination; however, there are diminishing returns to additional positive DDs.

Infection transmission and chronic disease models in the study of infection-associated cancers

In the last three decades, the appreciation of the role of infections in cancer aetiology has greatly expanded. Among the 13 million new cancer cases that occurred worldwide in 2008, around 2 million (16%) were attributable to infections. Concurrently, the approach to prevention of infection-related cancers is shifting from cancer control to infection control, for example, vaccination and the detection of infected individuals. In support of this change, the use of infection transmission models has entered the field of infection-related cancer epidemiology. These models are useful to understand the infection transmission processes, to estimate the key parameters that govern the spread of infection, and to project the potential impact of different preventive measures. However, the concepts, terminology, and methods used to study infection transmission are not yet well known in the domain of cancer epidemiology. This review aims to concisely illustrate the main principles of transmission dynamics, the basic structure of infection transmission models, and their use in combination with empirical data. We also briefly summarise models of carcinogenesis and discuss their specificities and possible integration with models of infection natural history.

Trends in the Risk of U.S. Polio Outbreaks and Poliovirus Vaccine Availability for Response

The United States eliminated indigenous wild polioviruses (WPVs) in 1979 and switched to inactivated poliovirus vaccine in 2000, which quickly ended all indigenous live poliovirus transmission. Continued WPV circulation and use of oral poliovirus vaccine globally allow for the possibility of reintroduction of these viruses. We evaluated the risk of a U.S. polio outbreak and explored potential vaccine needs for outbreak response. We synthesized information available on vaccine coverage, exemptor populations, and population immunity. We used an infection transmission model to explore the potential dynamics of a U.S. polio outbreak and potential vaccine needs for outbreak response, and assessed the impacts of heterogeneity in population immunity for two different subpopulations with potentially low coverage. Although the risk of poliovirus introduction remains real, widespread transmission of polioviruses appears unlikely in the U.S., given high routine coverage. However, clusters of un- or underimmunized children might create pockets of susceptibility that could potentially lead to one or more paralytic polio cases. We found that the shift toward combination vaccine utilization, with limited age indications for use, and other current trends (e.g., decreasing proportion of the population with immunity induced by live polioviruses and aging of vaccine exemptor populations) might increase the vulnerability to poliovirus reintroduction at the same time that the ability to respond may decrease. The U.S. poliovirus vaccine stockpile remains an important resource that may potentially be needed in the future to respond to an outbreak if a live poliovirus gets imported into a subpopulation with low vaccination coverage.

Economic analysis of the global polio eradication initiative

The global polio eradication initiative (GPEI), which started in 1988, represents the single largest, internationally coordinated public health project to date. Completion remains within reach, with type 2 wild polioviruses apparently eradicated since 1999 and fewer than 2000 annual paralytic poliomyelitis cases of wild types 1 and 3 reported since then. This economic analysis of the GPEI reflects the status of the program as of February 2010, including full consideration of post-eradication policies. For the GPEI intervention, we consider the actual pre-eradication experience to date followed by two distinct potential future post-eradication vaccination policies. We estimate GPEI costs based on actual and projected expenditures and poliomyelitis incidence using reported numbers corrected for underreporting and model projections. For the comparator, which assumes only routine vaccination for polio historically and into the future (i.e., no GPEI), we estimate poliomyelitis incidence using a dynamic infection transmission model and costs based on numbers of vaccinated children. Cost-effectiveness ratios for the GPEI vs. only routine vaccination qualify as highly cost-effective based on standard criteria. We estimate incremental net benefits of the GPEI between 1988 and 2035 of approximately 40–50billion dollars (2008 US dollars; 1988 net present values). Despite the high costs of achieving eradication in low-income countries, low-income countries account for approximately 85% of the total net benefits generated by the GPEI in the base case analysis. The total economic costs saved per prevented paralytic poliomyelitis case drive the incremental net benefits, which become positive even if we estimate the loss in productivity as a result of disability as below the recommended value of one year in average per-capita gross national income per disability-adjusted life year saved. Sensitivity analysis suggests that the finding of positive net benefits of the GPEI remains robust over a wide range of assumptions, and that consideration of the additional net benefits of externalities that occurred during polio campaigns to date, such as the mortality reduction associated with delivery of Vitamin A supplements, significantly increases the net benefits. This study finds a strong economic justification for the GPEI despite the rising costs of the initiative.

To what extent is the HIV epidemic in southern India driven by commercial sex? A modelling analysis

In south India, general population HIV prevalence estimates range from 0.5 to 3%. To focus HIV prevention efforts, it is important to understand whether HIV transmission is driven by commercial sex. A dynamic HIV/sexually transmitted infection transmission model was parameterized using data from Belgaum and Mysore in south India. Fits to sexually transmitted infection/HIV data from female sex workers (FSWs) and their clients for each district were obtained. Model HIV/herpes simplex virus-2 (HSV-2) prevalence projections for the general population were cross-validated against empirical estimates not used to fit model. The model estimated the proportion of incident HIV/HSV-2 infections due to HIV/HSV-2 transmission between FSWs/clients, their noncommercial partners and other low-risk partnerships. The relative impact of a generic intervention targeting different partnerships was explored. The model's general population HIV/HSV-2 prevalence projections agreed well with empirical estimates. Recent increases in condom use resulted in decreasing HIV epidemics in both settings. For men, most incident HIV/HSV-2 infections (>90%) directly result from commercial sex, whereas for women most are due to bridging infections from clients of FSWs (80-90%) with the remainder mainly due to commercial sex. Less than 1.5% of incident infections are due to low-risk partnerships. Intervention impact is maximized through targeting commercial sex but substantial impact could also be achieved through targeting noncommercial partners of clients. In southern India, HIV transmission could be driven by FSWs and their clients. While efforts to reduce HIV transmission due to commercial sex must continue, prevention programmes should also consider strategies to prevent transmission from clients to their noncommercial partners.

Individual causal models and population system models in epidemiology.

A group of individuals behaves as a population system when patterns of connections among individuals influence population health outcomes. Epidemiology usually treats populations as collections of independent individuals rather than as systems of interacting individuals. An appropriate theoretical structure, which includes the determinants of connections among individuals, is needed to develop a "population system epidemiology." Infection transmission models and sufficient-component cause models provide contrasting templates for the needed theoretical structure. Sufficient-component cause models focus on joint effects of multiple exposures in individuals. They handle time and interactions between individuals in the definition of variables and assume that populations are the sum of their individuals. Transmission models, in contrast, model interactions among individuals over time. Their nonlinear structure means that population risks are not simply the sum of individual risks. The theoretical base for "population system epidemiology" should integrate both approaches. It should model joint effects of multiple exposures in individuals as time related processes while incorporating the determinants and effects of interactions among individuals. Recent advances in G-estimation and discrete individual transmission model formulation provide opportunities for such integration.