UNASSIGNED: As the societal value of vaccines is increasingly recognized, there is a need to examine methodological approaches that could be used to integrate these various benefits in the economic evaluation of a vaccine.
UNASSIGNED: A literature review and two expert panel meetings explored methodologies to value herd immunity, health spillover effects (beyond herd immunity), impact on antimicrobial resistance, productivity and equity implications of vaccines.
UNASSIGNED: The consideration of broader benefits of vaccines in economic evaluation is complicated and necessitates technical expertise. Whereas methodologies to account for herd immunity and work productivity are relatively well established, approaches to investigate equity implications are developing and less frequently applied. Modelling the potential impact on antimicrobial resistance not only depends on the multi-faceted causal relationship between vaccination and resistance, but also on data availability.
UNASSIGNED: Different methods are available to value the broad impact of vaccines and it is important that analysts are aware of their strengths and limitations and justify their choice of method. In the future, we expect that an increasing number of economic evaluations will consider the broader benefits of vaccines as part of their base-case analysis or in sensitivity analyses.

Public health systems reported low mortality from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in East Asia, in low-income countries, and for children during the first year of the SARS-CoV-2 pandemic. These reports led commentators to suggest that cross-reactive immunity from prior exposure to other pathogens reduced fatality risk. Resolution of initial infection waves also contributed to speculation that herd immunity prevented further waves prior to vaccination. Serology instead implied that immunity was too limited to achieve herd immunity and that there was little impact from cross-reactive protection. Paediatric deaths exceeded those from influenza, with higher age-specific fatality risk in lower-income nations and similar fatality risk in East Asia compared with demographically similar regions. Neither pre-outbreak exposure to related pathogens nor immunity induced by initial infection waves are necessarily a reliable response to future pathogen outbreaks. Preparedness for future pathogen outbreaks should instead focus on strategies such as voluntary behavioural changes, nonpharmaceutical interventions, and vaccination.

UNASSIGNED: To combat the hesitancy towards implementing a hepatitis A universal mass vaccination (UMV) strategy and to provide healthcare authorities with a comprehensive analysis of the potential outcomes and benefits of the implementation of such a vaccination program, we projected HAV seroprevalence and incidence rates in the total population of the Russian Federation and estimated the pediatric vaccination threshold required to achieve an incidence level of less than 1 case per 100,000 using a new mathematical model.
UNASSIGNED: A dynamic age-structured SEIRV (susceptible-exposed-infectious-recovered-vaccinated) compartmental model was developed and calibrated using demographic, seroprevalence, vaccination, and epidemiological data from different regions of the Russian Federation. This model was used to project various epidemiological measures.
UNASSIGNED: The projected national average age at the midpoint of population immunity increases from 40 years old in 2020 to 50 years old in 2036 and is shifted even further to the age of 70 years in some regions of the country. An increase of varying magnitude in the incidence of symptomatic HAV infections is predicted for all study regions and for the Russian Federation as a whole between 2028 and 2032, if the HAV vaccination coverage level remains at the level of 2022. The national average vaccination coverage level required to achieve a symptomatic HAV incidence rate below 1 case per 100,000 by 2032 was calculated to be 69.8% if children aged 1-6 years are vaccinated following the implementation of a UMV program or 34.8% if immunization is expanded to children aged 1-17 years.
UNASSIGNED: The developed model provides insights into a further decline of herd immunity to HAV against the background of ongoing viral transmission. The current favorable situation regarding hepatitis A morbidity is projected to be replaced by an increase in incidence rates if vaccination coverage remains at the current levels. The obtained results support the introduction of a hepatitis A UMV strategy in the Russian Federation.

UNASSIGNED: The prevailing unwillingness to accept COVID-19 vaccination among the eligible population has been a serious setback in Nigeria\'s bid to reach herd immunity against the pandemic.
UNASSIGNED: We assessed the impact of a multidisciplinary health communication intervention (MHCI) on willingness to accept COVID-19 vaccination among eligible unvaccinated community dwellers (EUCD) in Nsukka Urban, Enugu State, Nigeria.
UNASSIGNED: Through a quasi-experiment that adopted a pre-test, post-test, non-control group design, we studied a total of 85 eligible unvaccinated adults. A researcher-designed \"Willingness to Accept COVID-19 Vaccination Questionnaire\" was the instrument used for data collection. The data gathered was analysed by means of Statistical Package for Social Sciences (SPSS) version 23.0. Specifically, descriptive and inferential statistics were used to test the formulated research questions and the hypothesis at 0.05 level of significance.
UNASSIGNED: We found that the mean scores of willingness to accept COVID-19 vaccination increased significantly after the treatment. There was no significant interaction effect of gender, level of education, and age on the mean of willingness to accept COVID-19 vaccination scores of EUCD after MHCI.
UNASSIGNED: The study established that MHCI is impactful in bolstering the willingness to accept COVID-19 vaccination. The Nigerian government should adopt and implement this intervention in schools, communities, and other institutions in order to attain herd immunity in Nigeria.

BACKGROUND: Now and in the future, airborne diseases such as COVID-19 could become uncontrollable and lead the world into lockdowns. Finding alternatives to lockdowns, which limit individual freedoms and cause enormous economic losses, is critical.
OBJECTIVE: The purpose of this study was to assess the feasibility of achieving a society or a nation that does not require lockdown during a pandemic due to airborne infectious diseases through the mass production and distribution of high-performance, low-cost, and comfortable powered air purifying respirators (PAPRs).
METHODS: The feasibility of a social system using PAPR as an alternative to lockdown was examined from the following perspectives: first, what PAPRs can do as an alternative to lockdown; second, how to operate a social system utilizing PAPR; third, directions of improvement of PAPR as an alternative to lockdown; and finally, balancing between efficiency of infection control and personal freedom through the use of Internet of Things (IoT).
RESULTS: PAPR was shown to be a possible alternative to lockdown through the reduction of airborne and droplet transmissions and through a temporary reduction of infection probability per contact. A social system in which individual constraints imposed by lockdown are replaced by PAPRs was proposed, and an example of its operation is presented in this paper. For example, the government determines the type and intensity of the lockdown and activates it. At that time, the government will also indicate how PAPR can be substituted for the different activity and movement restrictions imposed during a lockdown, for example, a curfew order may be replaced with the permission to go outside if wearing a PAPR. The following 7 points were raised as directions for improvement of PAPR as an alternative method to lockdown: flow optimization, precise differential pressure control, design improvement, maintenance method, variation development such as booth type, information terminal function, and performance evaluation method. In order to achieve the effectiveness and efficiency in controlling the spread of infection and the individual freedom at a high level in a social system that uses PAPRs as an alternative to lockdown, it was considered effective to develop a PAPR wearing rate network management system utilizing IoT.
CONCLUSIONS: This study shows that using PAPR with infection control ability and with less economic and social damage as an alternative to nationwide lockdown is possible during a pandemic due to airborne infectious diseases. Further, the efficiency of the government\'s infection control and each citizen\'s freedom can be balanced by using the PAPR wearing rate network management system utilizing an IoT system.

BACKGROUND: COVID-19 may become a seasonal disease. SARS-CoV-2 active circulation coupled with vaccination efforts has undoubtedly modified the virus dynamic. It is therefore important investigate SARS-CoV-2 dynamic in different groups of population following the course of spatiotemporal variance and immunization.
METHODS: To investigate SARS-CoV-2 clearance in different ethnic groups and the impact of immunization, we recruited 777 SARS-CoV-2-positive patients (570 Africans, 156 Caucasians, and 51 Asians). Participants were followed and regularly tested for 2 months until they had two negative tests.
RESULTS: The vaccination rate was 64.6%. African individuals were less symptomatic (2%), Caucasians (41%) and Asians (36.6%). On average, viral clearance occurred after 10.5 days. Viral load at diagnosis was inversely correlated with viral clearance (p < 0.0001). The time of SARS-CoV-2 clearance was higher in Africans and Caucasians than in Asians (Dunn\'s test p < 0.0001 and p < 0.05, respectively). On average, viral clearance occurred within 9.5 days during the second semester (higher rate of vaccination and SARS-CoV-2 exposition), whereas it took 13.6 days during the first semester (lower rate of vaccination and SARS-CoV-2 exposition) (Mann-Whitney t-test p < 0.0001).
CONCLUSIONS: In conclusion, ethnicity and spatiotemporal changes including SARS-CoV-2 exposition and immunization affect SARS-CoV-2 clearance.

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Assessing population-level effects of vaccines and other infectious disease prevention measures is important to the field of public health. In infectious disease studies, one person\'s treatment may affect another individual\'s outcome, that is, there may be interference between units. For example, the use of bed nets to prevent malaria by one individual may have an indirect effect on other individuals living in close proximity. In some settings, individuals may form groups or clusters where interference only occurs within groups, that is, there is partial interference. Inverse probability weighted estimators have previously been developed for observational studies with partial interference. Unfortunately, these estimators are not well suited for studies with large clusters. Therefore, in this paper, the parametric g-formula is extended to allow for partial interference. G-formula estimators are proposed for overall effects, effects when treated, and effects when untreated. The proposed estimators can accommodate large clusters and do not suffer from the g-null paradox that may occur in the absence of interference. The large sample properties of the proposed estimators are derived assuming no unmeasured confounders and that the partial interference takes a particular form (referred to as \'weak stratified interference\'). Simulation studies are presented demonstrating the finite-sample performance of the proposed estimators. The Demographic and Health Survey from the Democratic Republic of the Congo is then analyzed using the proposed g-formula estimators to assess the effects of bed net use on malaria.

The COVID-19 pandemic, caused by SARS-CoV-2, disproportionately affected certain segments of society, particularly the elderly population (which suffered the brunt of the burden of the pandemic in terms of severity of the disease, hospitalization, and death). This study presents a generalized multigroup model, with m heterogeneous sub-populations, to assess the population-level impact of age heterogeneity and vaccination on the transmission dynamics and control of the SARS-CoV-2 pandemic in the United States. Rigorous analysis of the model for the homogeneous case (i.e., the model with m = 1) reveal that its disease-free equilibrium is globally-asymptotically stable for two special cases (with perfect vaccine efficacy or negligible disease-induced mortality) whenever the associated reproduction number is less than one. The model has a unique and globally-asymptotically stable endemic equilibrium, for special a case, when the associated reproduction threshold exceeds one. The homogeneous model was fitted using the observed cumulative mortality data for the United States during three distinct waves (Waves A (October 17, 2020 to April 5, 2021), B (July 9, 2021 to November 7, 2021) and C (January 1, 2022 to May 7, 2022)) chosen to align with time periods when the Alpha, Delta and Omicron were, respectively, the predominant variants in the United States. The calibrated model was used to derive a theoretical expression for achieving vaccine-derived herd immunity (needed to eliminate the disease in the United States). It was shown that, using the one-group homogeneous model, vaccine-derived herd immunity is not attainable during Wave C of the pandemic in the United States, regardless of the coverage level of the fully-vaccinated individuals. Global sensitivity analysis was carried out to determine the parameters of the model that have the most influence on the disease dynamics and burden. These analyses reveal that control and mitigation strategies that may be very effective during one wave may not be so very effective during the other wave or waves. However, strategies that target asymptomatic and pre-symptomatic infectious individuals are shown to be consistently effective across all waves. To study the impact of the disproportionate effect of COVID-19 on the elderly population, we considered the heterogeneous model for the case where the total population is subdivided into the sub-populations of individuals under 65 years of age and those that are 65 and older. The resulting two-group heterogeneous model, which was also fitted using the cumulative mortality data for wave C, was also rigorously analysed. Unlike for the case of the one-group model, it was shown, for the two-group model, that vaccine-derived herd immunity can indeed be achieved during Wave C of the pandemic if at least 61% of the populace is fully vaccinated. Thus, this study shows that adding age heterogeneity into a SARS-CoV-2 vaccination model with homogeneous mixing significantly reduces the level of vaccination coverage needed to achieve vaccine-derived herd immunity (specifically, for the heterogeneous model, herd-immunity can be attained during Wave C if a moderate proportion of susceptible individuals are fully vaccinated). The consequence of this result is that vaccination models for SARS-CoV-2 that do not explicitly account for age heterogeneity may be overestimating the level of vaccine-derived herd immunity threshold needed to eliminate the SARS-CoV-2 pandemic.

Antibody responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are multi-targeted and variable over time. Multiplex quantitative serological assays are needed to provide accurate and robust seropositivity data for the establishment of serological signatures during vaccination and or infection. We describe here the validation and evaluation of an electro-chemiluminescence (ECL)-based Mesoscale Discovery assay (MSD) for estimation of total and functional IgG relative to SARS-CoV-2 spike, nucleocapsid and receptor binding (RBD) proteins in human serum samples to establish serological signatures of SARS-CoV-2 natural infection and breakthrough cases. The 9-PLEX assay was validated as per ICH, EMA, and US FDA guidelines using a panel of sera samples, including the NIBSC/WHO reference panel (20/268). The assay demonstrated high specificity and selectivity in inhibition assays, wherein the homologous inhibition was more than 85% and heterologous inhibition was below 10%. The assay also met predetermined acceptance criteria for precision (CV < 20%), accuracy (70-130%) and dilutional linearity. The method\'s applicability to serological signatures was demonstrated using sera samples (n = 45) representing vaccinated, infected and breakthrough cases. The method was able to establish distinct serological signatures and thus provide a potential tool for seroprevalence of SARS-CoV-2 during vaccination or infection.