Numerical Simulation of the COVID-19 Herd Immunity Based on Complex Network Modeling

Constructing an epidemic dynamic model and exploring the spreading law of epidemic have very important theoretical significance for epidemic prevention and control. Based on the existing homogeneous mixing model, in view of the increasingly obvious heterogeneity of individual contact relationships, and each individual is in a different contact relationship, a dynamic small-world network model that takes into account individual status. Contact tracking has been established to simulate the spread of the COVID-19 in society. By comparing the simulation results, the rationality of the built model is explained. On this basis, the simulation calculated the impact of the network topology and the proportion of vaccinated people on the spread of the COVID-19, analyzed the critical value of herd immunity. The established propagation model is reasonable, and feasible to achieve herd immunization by vaccination. © 2023 Editorial Borad of Complex Systems and Complexity Science. All rights reserved.

Projecting the Electricity Demand of the Residential Sector in Thailand During and After the COVID-19 Pandemic

The residential sector in Thailand has been a fast-growing energy consumption sector since 1995 at a rate of 6% per year. This sector makes a significant contribution to Thailand's rising electricity demand especially during the COVID-19 pandemic. This study projects Thailand's residential electricity consumption characteristics and the factors affecting the growth of electricity consumption using a system dynamics (SD) modeling approach to forecast long-term electricity consumption in Thailand. Furthermore, the COVID-19 pandemic and the lockdown can be seen as a forced social experiment, with the findings demonstrating how to use resources under particular circumstances. Four key factors affecting the electricity demand used in the SD model development include (1) work and study from home, (2) socio-demographic, (3) temperature changing, and (4) rise of GDP. Secondary and primary data, through questionnaire survey method, were used as data input for the model. The simulation results reveal that changing behavior on higher-wattage appliances has huge impacts on overall electricity consumption. The pressure to work and study at home contributes to rises of electricity consumption in the residential sector during and after COVID-19 pandemic. The government and related agencies may use the study results to plan for the electricity supply in the long term. © 2023 World Scientific Publishing Co.

The impact of disruptions caused by the COVID-19 pandemic on global polio eradication.

In early 2020, the COVID-19 pandemic led to substantial disruptions in global activities. The disruptions also included intentional and unintentional reductions in health services, including immunization campaigns against the transmission of wild poliovirus (WPV) and persistent serotype 2 circulating vaccine-derived poliovirus (cVDPV2). Building on a recently updated global poliovirus transmission and Sabin-strain oral poliovirus vaccine (OPV) evolution model, we explored the implications of immunization disruption and restrictions of human interactions (i.e., population mixing) on the expected incidence of polio and on the resulting challenges faced by the Global Polio Eradication Initiative (GPEI). We demonstrate that with some resumption of activities in the fall of 2020 to respond to cVDPV2 outbreaks and full resumption on January 1, 2021 of all polio immunization activities to pre-COVID-19 levels, the GPEI could largely mitigate the impact of COVID-19 to the delays incurred. The relative importance of reduced mixing (leading to potentially decreased incidence) and reduced immunization (leading to potentially increased expected incidence) depends on the timing of the effects. Following resumption of immunization activities, the GPEI will likely face similar barriers to eradication of WPV and elimination of cVDPV2 as before COVID-19. The disruptions from the COVID-19 pandemic may further delay polio eradication due to indirect effects on vaccine and financial resources.

Serotype 2 oral poliovirus vaccine (OPV2) choices and the consequences of delaying outbreak response.

The Global Polio Eradication Initiative (GPEI) faces substantial challenges with managing outbreaks of serotype 2 circulating vaccine-derived polioviruses (cVDPV2s) in 2021. A full five years after the globally coordinated removal of serotype 2 oral poliovirus vaccine (OPV2) from trivalent oral poliovirus vaccine (tOPV) for use in national immunization programs, cVDPV2s did not die out. Since OPV2 cessation, responses to outbreaks caused by cVDPV2s mainly used serotype 2 monovalent OPV (mOPV2) from a stockpile. A novel vaccine developed from a genetically stabilized OPV2 strain (nOPV2) promises to potentially facilitate outbreak response with lower prospective risks, although its availability and properties in the field remain uncertain. Using an established global poliovirus transmission model and building on a related analysis that characterized the impacts of disruptions in GPEI activities caused by the COVID-19 pandemic, we explore the implications of trade-offs associated with delaying outbreak response to avoid using mOPV2 by waiting for nOPV2 availability (or equivalently, delayed responses waiting for national validation of meeting the criteria for nOPV2 initial use). Consistent with prior modeling, responding as quickly as possible with available mOPV2 promises to reduce the expected burden of disease in the outbreak population and to reduce the chances for the outbreak virus to spread to other areas. Delaying cVDPV2 outbreak response (e.g., modeled as no response January-June 2021) to wait for nOPV2 can considerably increase the total expected cases (e.g., by as many as 1,300 cVDPV2 cases in the African region during 2021-2023) and increases the likelihood of triggering the need to restart widescale preventive use of an OPV2-containing vaccine in national immunization programs that use OPV. Countries should respond to any cVDPV2 outbreaks quickly with rounds that achieve high coverage using any available OPV2, and plan to use nOPV2, if needed, once it becomes widely available based on evidence that it is as effective but safer in populations than mOPV2.

Dynamic modeling of the Italians' attitude towards Covid-19.

We analyze repeated cross-sectional survey data collected by the Institute of Global Health Innovation, to characterize the perception and behavior of the Italian population during the Covid-19 pandemic, focusing on the period that spans from April 2020 to July 2021. To accomplish this goal, we propose a Bayesian dynamic latent-class regression model, that accounts for the effect of sampling bias including survey weights into the likelihood function. According to the proposed approach, attitudes towards covid-19 are described via ideal behaviors that are fixed over time, corresponding to different degrees of compliance with spread-preventive measures. The overall tendency toward a specific profile dynamically changes across survey waves via a latent Gaussian process regression, that adjusts for subject-specific covariates. We illustrate the evolution of Italians' behaviors during the pandemic, providing insights on how the proportion of ideal behaviors has varied during the phases of the lockdown, while measuring the effect of age, sex, region and employment of the respondents on the attitude toward covid-19.

Water Consumption in Portoviejo City from Pacific of Ecuador, During the Period 2017–2020 in the Context of the Health Crisis of SARS - CoV-2

Since March 2020, Ecuador has been in a health crisis due to the COVID-19 pandemic that resulted in confinement from March 17 to September 13, 2020. For this reason, the objective of the work was to perform an analysis of the volumes of drinking water recorded by the Decentralized Autonomous Government of Portoviejo, to determine whether the confinement phase determined an increase in the consumption of drinking water in the Portoviejo city. The information was obtained, from January 2017 to December 2020, from the water administration company named Portoaguas. An analysis of variances was carried out, ANOVA that determined the absence of a significant water consumption variation between the months of confinement in the year 2020 and three years ago. In addition, with population data obtained from the Ecuadorian Institute of Statistics and Census (INEC), and infection rate calculated from the data recorded by the Ministry of Health, we conducted a modeling population to obtain the endowments daily consumption in Portoviejo, which showed an increase of up to 16,28% in April 2020, but a decrease in May and August of the same year, concluding that the pandemic did not influence the consumption of water. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

On the COVID-19 Temporal Evolution in Brazil

This paper has two main objectives. The first one is to present a new dynamic model that describes, with adequate precision, the temporal behavior of the coronavirus epidemic that currently occurs in Brazil. Every day, the number of new infections provided by the Brazilian Ministry of Health is taken into account. Thus, an assessment of the impact of social behavior on the evolution of the epidemic can also be made. The second objective is to analyze the need to develop a computational system, capable of simulating—with the Monte Carlo method—the dynamic behavior of epidemics allowing each individual to move through locations with different population densities. © 2022, Springer Nature Switzerland AG.

Evaluation of simulation modeling of university dining hall COVID-19 reopening plans

The COVID-19 pandemic is reshaping and complicating the world. Nowhere has it been more controversial and complex than in reopening plans for schools. Observing student behavior indicates that the dining hall services are a major area of concern in reopening plans. Careful consideration and focus need to be taken into account for dealing with high demands in short timeframes experienced at dining halls. The removal of masks while eating increases the probability of spreading germs between individuals, forming a potential hotspot for spreading if a breakout were to occur. The dining halls are a complex system, in which modeling student behavior becomes critical conditions for determining results. Using Simio, a simulation and modeling software, three dining hall models were created and analyzed to determine the optimal number of people that should be allowed into the system where COVID-19 protocols could be followed but did not cause workstations to be idle. Parameters for the simulations were created from student conducted time studies. Simulation provided the ability to effectively compare alternative models with different conditions. Cycle time as well as queuing time and length were calculated for each model, which indicated the effectiveness of the system on meeting demand. The instructional models were compared to the baseline model to validate the dining hall COVID-19 reopening policies. The analysis proved guidelines for the dining halls would help limit the number of close contacts and get students through the system quickly;overall helping campus dining services serve students safely and quickly. © 2021 IISE Annual Conference and Expo 2021. All rights reserved.

A Multimodal Approach for the Risk Prediction of Intensive Care and Mortality in Patients with COVID-19.

BACKGROUND: Although several studies have been launched towards the prediction of risk factors for mortality and admission in the intensive care unit (ICU) in COVID-19, none of them focuses on the development of explainable AI models to define an ICU scoring index using dynamically associated biological markers. METHODS: We propose a multimodal approach which combines explainable AI models with dynamic modeling methods to shed light into the clinical features of COVID-19. Dynamic Bayesian networks were used to seek associations among cytokines across four time intervals after hospitalization. Explainable gradient boosting trees were trained to predict the risk for ICU admission and mortality towards the development of an ICU scoring index. RESULTS: Our results highlight LDH, IL-6, IL-8, Cr, number of monocytes, lymphocyte count, TNF as risk predictors for ICU admission and survival along with LDH, age, CRP, Cr, WBC, lymphocyte count for mortality in the ICU, with prediction accuracy 0.79 and 0.81, respectively. These risk factors were combined with dynamically associated biological markers to develop an ICU scoring index with accuracy 0.9. CONCLUSIONS: to our knowledge, this is the first multimodal and explainable AI model which quantifies the risk of intensive care with accuracy up to 0.9 across multiple timepoints.

Globalized inclination to acquire knowledge and skills toward economic development

In an era of economic recession and the divulged threats of COVID-19 pandemic in the world a highly impacting socio-economic activity is the education sector. The operational difficulties of companies and organizations, as well as the closure of universities, schools, training courses, are all affecting the entrepreneurial and the learning progress on using workers time and learners facilities to develop their knowledge and to build up their skills. In particular, free time of institutions’ closure can become a golden opportunity for learning and progresses in virtual education while adopting e-learning modes of information technology (IT) and supporting the distribution of knowledge and information for training and education. Since the COVID-19 pandemic outbreak only few studies have been devoted on studying the impact of cultural characteristics, economic situations, skills and knowledge on the development and the wider human wellbeing. At this study the literature production of economic development was investigated in the light of the ignored, but critically important, issue of globalized inclination to acquire knowledge and skills. All essential aspects of economic systems and economic development within the COVID-19 era were approached, quantified, and graphically valuated, in the light of the following fields of literature search: “dynamic economic systems”, “economic development”, “knowledge skills”, and “globalization”. The measurable indicators of comparing these results were that of: chronological, geographical, languages of reports’ written, subject areas, and keywords, accordingly. Besides, the three domains of technology, environment – ecology, and socio-economics were conveyed, while the key-determinants of knowledge and skills acquisition were also analyzed. From a managerial point of view the simultaneous affection of cultural characteristics, economic simulations, skills and knowledge aspects were considered as positive and significant, thus, supporting managers to better understand the necessities of IT development and managing a highly qualified workforce to shift the thread of the COVID-19 era while performing feasible learning management to solidify workers’ education through formal and in-house education. © 2021, World Scientific and Engineering Academy and Society. All rights reserved.

Updated Characterization of Poliovirus Transmission in Pakistan and Afghanistan and the Impacts of Different Outbreak Response Vaccine Options.

BACKGROUND: Pakistan and Afghanistan remain the only reservoirs of wild poliovirus transmission. Prior modeling suggested that before the coronavirus disease 2019 (COVID-19) pandemic, plans to stop the transmission of serotype 1 wild poliovirus (WPV1) and persistent serotype 2 circulating vaccine-derived poliovirus (cVDPV2) did not appear on track to succeed. METHODS: We updated an existing poliovirus transmission and Sabin-strain oral poliovirus vaccine (OPV) evolution model for Pakistan and Afghanistan to characterize the impacts of immunization disruptions and restrictions on human interactions (ie, population mixing) due to the COVID-19 pandemic. We also consider different options for responding to outbreaks and for preventive supplementary immunization activities (SIAs). RESULTS: The modeling suggests that with some resumption of activities in the fall of 2020 to respond to cVDPV2 outbreaks and full resumption on 1 January 2021 of all polio immunization activities to pre-COVID-19 levels, Pakistan and Afghanistan would remain off-track for stopping all transmission through 2023 without improvements in quality. CONCLUSIONS: Using trivalent OPV (tOPV) for SIAs instead of serotype 2 monovalent OPV offers substantial benefits for ending the transmission of both WPV1 and cVDPV2, because tOPV increases population immunity for both serotypes 1 and 2 while requiring fewer SIA rounds, when effectively delivered in transmission areas.

Updated Characterization of Outbreak Response Strategies for 2019-2029: Impacts of Using a Novel Type 2 Oral Poliovirus Vaccine Strain.

Delays in achieving the global eradication of wild poliovirus transmission continue to postpone subsequent cessation of all oral poliovirus vaccine (OPV) use. Countries must stop OPV use to end all cases of poliomyelitis, including vaccine-associated paralytic polio (VAPP) and cases caused by vaccine-derived polioviruses (VDPVs). The Global Polio Eradication Initiative (GPEI) coordinated global cessation of all type 2 OPV (OPV2) use in routine immunization in 2016 but did not successfully end the transmission of type 2 VDPVs (VDPV2s), and consequently continues to use type 2 OPV (OPV2) for outbreak response activities. Using an updated global poliovirus transmission and OPV evolution model, we characterize outbreak response options for 2019-2029 related to responding to VDPV2 outbreaks with a genetically stabilized novel OPV (nOPV2) strain or with the currently licensed monovalent OPV2 (mOPV2). Given uncertainties about the properties of nOPV2, we model different assumptions that appear consistent with the evidence on nOPV2 to date. Using nOPV2 to respond to detected cases may reduce the expected VDPV and VAPP cases and the risk of needing to restart OPV2 use in routine immunization compared to mOPV2 use for outbreak response. The actual properties, availability, and use of nOPV2 will determine its effects on type 2 poliovirus transmission in populations. Even with optimal nOPV2 performance, countries and the GPEI would still likely need to restart OPV2 use in routine immunization in OPV-using countries if operational improvements in outbreak response to stop the transmission of cVDPV2s are not implemented effectively.

Toward the Impact of Non-pharmaceutical Interventions and Vaccination on the COVID-19 Pandemic With Time-Dependent SEIR Model.

The outbreak of COVID-19, caused by the SARS-CoV-2 coronavirus, has been declared a pandemic by the World Health Organization (WHO) in March, 2020 and rapidly spread to over 210 countries and territories around the world. By December 24, there are over 77M cumulative confirmed cases with more than 1.72M deaths worldwide. To mathematically describe the dynamic of the COVID-19 pandemic, we propose a time-dependent SEIR model considering the incubation period. Furthermore, we take immunity, reinfection, and vaccination into account and propose the SEVIS model. Unlike the classic SIR based models with constant parameters, our dynamic models not only predicts the number of cases, but also monitors the trajectories of changing parameters, such as transmission rate, recovery rate, and the basic reproduction number. Tracking these parameters, we observe the significant decrease in the transmission rate in the U.S. after the authority announced a series of orders aiming to prevent the spread of the virus, such as closing non-essential businesses and lockdown restrictions. Months later, as restrictions being gradually lifted, we notice a new surge of infection emerges as the transmission rates show increasing trends in some states. Using our epidemiology models, people can track, timely monitor, and predict the COVID-19 pandemic with precision. To illustrate and validate our model, we use the national level data (the U.S.) and the state level data (New York and North Dakota), and the resulting relative prediction errors for the infected group and recovered group are mostly lower than 0.5%. We also simulate the long-term development of the pandemic based on our proposed models to explore when the crisis will end under certain conditions.

Expected Implications of Globally Coordinated Cessation of Serotype 3 Oral Poliovirus Vaccine (OPV) Before Serotype 1 OPV.

Globally coordinated cessation of all three serotypes of oral poliovirus vaccine (OPV) represents a critical part of a successful polio endgame, which the Global Polio Eradication Initiative (GPEI) plans to conduct in phases, with serotype 2 OPV cessation completed in mid 2016. Although in 2016 the GPEI expected to globally coordinate cessation of the remaining OPV serotypes (1 and 3) by 2021, continuing transmission of serotype 1 wild polioviruses to date makes those plans obsolete. With increasing time since the last reported polio case caused by serotype 3 wild poliovirus (in November 2012) leading to high confidence about its successful global eradication, the Global Commission for the Certification of Poliomyelitis Eradication recently certified its eradication. Questions now arise about the optimal timing of serotype 3 OPV (OPV3) cessation. Using an integrated global model that characterizes the risks, costs, and benefits of global polio policy and risk management options, we explored the implications of different options for coordinated cessation of OPV3 prior to COVID-19. Globally coordinating cessation of OPV3 as soon as possible offers the opportunity to reduce cases of vaccine-associated paralytic polio globally. In addition, earlier cessation of OPV3 should reduce the risks of creating serotype 3 circulating vaccine-derived polioviruses after OPV3 cessation, which represents a significant threat to the polio endgame given current GPEI plans to reduce preventive OPV supplemental immunization activities starting in 2019.

Hypothetical emergence of poliovirus in 2020: part 1. Consequences of policy decisions to respond using nonpharmaceutical interventions.

OBJECTIVES: As efforts to control COVID-19 continue, we simulate hypothetical emergence of wild poliovirus assuming an immunologically naïve population. This differs from the current global experience with polio and serves as a model for responding to future pandemics. METHODS: Applying an established global model, we assume a fully susceptible global population to polioviruses, independently introduce a virus with properties of each of the three stable wild poliovirus serotypes, and explore the impact of strategies that range from doing nothing to seeking global containment and eradication. RESULTS: We show the dynamics of paralytic cases as the virus spreads globally. We demonstrate the difficulty of eradication unless aggressive efforts begin soon after initial disease detection. Different poliovirus serotypes lead to different trajectories and burdens of disease. In the absence of aggressive measures, the virus would become globally endemic in 2-10 years, and cumulative paralytic cases would exceed 4-40 million depending on serotype, with the burden of disease shifting to younger ages. CONCLUSIONS: The opportunity to eradicate emerging infections represents an important public policy choice. If the world first observed the emergence of wild poliovirus in 2020, adopting aggressive control strategies would have been required to prevent a devastating global pandemic.

First two months of the 2019 Coronavirus Disease (COVID-19) epidemic in China: real-time surveillance and evaluation with a second derivative model.

Background: Similar to outbreaks of many other infectious diseases, success in controlling the novel 2019 coronavirus infection requires a timely and accurate monitoring of the epidemic, particularly during its early period with rather limited data while the need for information increases explosively. Methods: In this study, we used a second derivative model to characterize the coronavirus epidemic in China with cumulatively diagnosed cases during the first 2 months. The analysis was further enhanced by an exponential model with a close-population assumption. This model was built with the data and used to assess the detection rate during the study period, considering the differences between the true infections, detectable and detected cases. Results: Results from the second derivative modeling suggest the coronavirus epidemic as nonlinear and chaotic in nature. Although it emerged gradually, the epidemic was highly responsive to massive interventions initiated on January 21, 2020, as indicated by results from both second derivative and exponential modeling analyses. The epidemic started to decelerate immediately after the massive actions. The results derived from our analysis signaled the decline of the epidemic 14 days before it eventually occurred on February 4, 2020. Study findings further signaled an accelerated decline in the epidemic starting in 14 days on February 18, 2020. Conclusions: The coronavirus epidemic appeared to be nonlinear and chaotic, and was responsive to effective interventions. The methods used in this study can be applied in surveillance to inform and encourage the general public, public health professionals, clinicians and decision-makers to take coordinative and collaborative efforts to control the epidemic.