Vaccine Distribution Strategies Research Articles

“It’s another gay disease”: an intersectional qualitative approach contextualizing the lived experiences of young gay, bisexual, and other sexual minoritized men in the United States during the mpox outbreak

BackgroundThe U.S. mpox outbreak in 2022 introduced new and exacerbated existing challenges that disproportionately stigmatize gay, bisexual, and other sexual minoritized men (GBSMM). This study contextualizes the perceptions, susceptibility, and lived experiences of the mpox outbreak among GBSMM in the U.S. using an intersectional framework.MethodsBetween September 2022 to February 2023, we conducted 33 semi-structured qualitative interviews with purposively sampled GBSMM in the Northeast and the South region of the United States on various aspects related to their experience during the mpox outbreak.ResultsWe identified four themes: (1) understanding and conceptualizations of mpox, (2) mpox vaccine availability and accessibility, (3) mpox vaccine hesitancy and mistrust, and (4) call to action and recommendations. GBSMM collectively discussed the elevated mpox stigmatization and homophobic discourse from mainstream social media and news outlets. GBSMM also discussed the lack of availability of mpox vaccines, unclear procedures to receive the vaccine, and continued mistrust in government, non-government, and other institutions of health that were complicit in anti-LGBTQ + narratives related to mpox. However, they expressed that these challenges may be addressed through more LGTBQ + representation and leveraging ways to empower these communities.ConclusionGBSMM have mpox experiences that are distinct and multifaceted. Effectively addressing mpox and mitigating public health emergencies for GBSMM requires prioritizing destigmatizing communication channels and vaccine distribution strategies by centering their stories and lived experiences to advance health equity.

COVID-19 vaccination strategies in Africa: A scoping review of the use of mathematical models to inform policy.

Mathematical models are vital tools to understand transmission dynamics and assess the impact of interventions to mitigate COVID-19. However, historically, their use in Africa has been limited. In this scoping review, we assess how mathematical models were used to study COVID-19 vaccination to potentially inform pandemic planning and response in Africa. We searched six electronic databases: MEDLINE, Embase, Web of Science, Global Health, MathSciNet and Africa-Wide NiPAD, using keywords to identify articles focused on the use of mathematical modelling studies of COVID-19 vaccination in Africa that were published as of October 2022. We extracted the details on the country, author affiliation, characteristics of models, policy intent and heterogeneity factors. We assessed quality using 21-point scale criteria on model characteristics and content of the studies. The literature search yielded 462 articles, of which 32 were included based on the eligibility criteria. Nineteen (59%) studies had a first author affiliated with an African country. Of the 32 included studies, 30 (94%) were compartmental models. By country, most studies were about or included South Africa (n = 12, 37%), followed by Morocco (n = 6, 19%) and Ethiopia (n = 5, 16%). Most studies (n = 19, 59%) assessed the impact of increasing vaccination coverage on COVID-19 burden. Half (n = 16, 50%) had policy intent: prioritising or selecting interventions, pandemic planning and response, vaccine distribution and optimisation strategies and understanding transmission dynamics of COVID-19. Fourteen studies (44%) were of medium quality and eight (25%) were of high quality. While decision-makers could draw vital insights from the evidence generated from mathematical modelling to inform policy, we found that there was limited use of such models exploring vaccination impacts for COVID-19 in Africa. The disparity can be addressed by scaling up mathematical modelling training, increasing collaborative opportunities between modellers and policymakers, and increasing access to funding.

Strategies to strengthen COVID-19 vaccine uptake and improve vaccine equity in U.S. Territories and Freely Associated States during the first six months of vaccine rollout

The eight U.S. territories and freely associated states (TFAS) have historically faced unique social and structural barriers in the implementation of vaccination programs due to geographic remoteness, a high prevalence of socioeconomic disparities, increasing prevalence of natural disasters, limited vaccine providers and clinics, difficulties with procurement and shipping, and difficulty tracking highly mobile populations. In the months leading up to emergency authorizations for the use of COVID-19 vaccines, the TFAS developed tailored vaccination strategies to ensure that key at-risk populations received timely vaccination, and successfully implemented these strategies during the first six months of the vaccine rollout. Subject matter experts supporting the Centers for Disease Control and Prevention’s COVID-19 Response recognized the unique historical, geographic, social, and cultural dynamics for residents in the TFAS and worked with partners to prevent, detect, and respond to the pandemic in these jurisdictions. As a result of innovative partnerships and vaccine distribution strategies, vaccine equity was improved in the TFAS during the COVID-19 vaccine rollout.

Promoting Fair Vaccination Strategies through Influence Maximization: A Case Study on COVID-19 Spread

The aftermath of the Covid-19 pandemic saw more severe outcomes for racial minority groups and economically-deprived communities. Such disparities can be explained by several factors, including unequal access to healthcare, as well as the inability of low income groups to reduce their mobility due to work or social obligations. Moreover, senior citizens were found to be more susceptible to severe symptoms, largely due to age-related health reasons. Adapting vaccine distribution strategies to consider a range of demographics is therefore essential to address these disparities. In this study, we propose a novel approach that utilizes influence maximization (IM) on mobility networks to develop vaccination strategies which incorporate demographic fairness. By considering factors such as race, social status, age, and associated risk factors, we aim to optimize vaccine distribution to achieve various fairness definitions for one or more protected attributes at a time. Through extensive experiments conducted on Covid-19 spread in three major metropolitan areas across the United States, we demonstrate the effectiveness of our proposed approach in reducing disease transmission and promoting fairness in vaccination distribution.

Multi-feature SEIR model for epidemic analysis and vaccine prioritization.

The SEIR (susceptible-exposed-infected-recovered) model has become a valuable tool for studying infectious disease dynamics and predicting the spread of diseases, particularly concerning the COVID pandemic. However, existing models often oversimplify population characteristics and fail to account for differences in disease sensitivity and social contact rates that can vary significantly among individuals. To address these limitations, we have developed a new multi-feature SEIR model that considers the heterogeneity of health conditions (disease sensitivity) and social activity levels (contact rates) among populations affected by infectious diseases. Our model has been validated using the data of the confirmed COVID cases in Allegheny County (Pennsylvania, USA) and Hamilton County (Ohio, USA). The results demonstrate that our model outperforms traditional SEIR models regarding predictive accuracy. In addition, we have used our multi-feature SEIR model to propose and evaluate different vaccine prioritization strategies tailored to the characteristics of heterogeneous populations. We have formulated optimization problems to determine effective vaccine distribution strategies. We have designed extensive numerical simulations to compare vaccine distribution strategies in different scenarios. Overall, our multi-feature SEIR model enhances the existing models and provides a more accurate picture of disease dynamics. It can help to inform public health interventions during pandemics/epidemics.

Having a real say: findings from first nations community panels on pandemic influenza vaccine distribution

BackgroundRecent deliberations by Australian public health researchers and practitioners produced an ethical framework of how decisions should be made to distribute pandemic influenza vaccine. The outcome of the deliberations was that the population should be considered in two categories, Level 1 and Level 2, with Level 1 groups being offered access to the pandemic influenza vaccine before other groups. However, the public health researchers and practitioners recognised the importance of making space for public opinion and sought to understand citizens values and preferences, especially First Nations peoples.MethodsWe conducted First Nations Community Panels in two Australian locations in 2019 to assess First Nations people’s informed views through a deliberative process on pandemic influenza vaccination distribution strategies. Panels were asked to make decisions on priority levels, coverage and vaccine doses.ResultsTwo panels were conducted with eighteen First Nations participants from a range of ages who were purposively recruited through local community networks. Panels heard presentations from public health experts, cross-examined expert presenters and deliberated on the issues. Both panels agreed that First Nations peoples be assigned Level 1 priority, be offered pandemic influenza vaccination before other groups, and be offered two doses of vaccine. Reasons for this decision included First Nations people’s lives, culture and families are important; are at-risk of severe health outcomes; and experience barriers and challenges to accessing safe, quality and culturally appropriate healthcare. We found that communication strategies, utilising and upskilling the First Nations health workforce, and targeted vaccination strategies are important elements in pandemic preparedness and response with First Nations peoples.ConclusionsFirst Nations Community Panels supported prioritising First Nations peoples for pandemic influenza vaccination distribution and offering greater protection by using a two-dose full course to fewer people if there are initial supply limitations, instead of one dose to more people, during the initial phase of the vaccine roll out. The methodology and findings can help inform efforts in planning for future pandemic vaccination strategies for First Nations peoples in Australia.

Need for open data on COVID-19 vaccine uptake among pregnant people in the Caribbean: a call to action.

Pregnant people with coronavirus disease 2019 (COVID-19) have a higher risk of adverse maternal and fetal outcomes compared with pregnant people without COVID-19. In 2021, large increases in maternal mortality were reported in Jamaica, almost half of which were attributable to COVID-19. COVID-19 vaccination has been shown to reduce these risks, but low- and middle-income countries lack free, publicly available data, known as open data, on COVID-19 vaccine uptake for their pregnant populations. The objectives of this paper were to: review how high-income countries use open data to detect trends in COVID-19 vaccine uptake among pregnant people and develop vaccination distribution strategies; outline barriers to making open data available for maternal COVID-19 vaccination in the Caribbean; and propose a multipronged strategy that would increase the availability of open data on maternal COVID-19 vaccination in the Caribbean. A multipronged strategy to fill the data void would involve: (i) utilizing existing Caribbean maternal immunization data collection entities; (ii) adapting digital software tools to establish maternal electronic immunization registries; and (iii) collaborating with local partners skilled in data analytics. Making open data available for COVID-19 vaccine uptake among pregnant people in the Caribbean could offer substantial benefits, including the development of measurable maternal COVID-19 vaccination goals and the facilitation of vaccine decision-making discussions between providers and pregnant people.

What are effective vaccine distribution approaches for equity-deserving and high-risk populations during COVID-19? Exploring best practices and recommendations in Canada: protocol for a mixed-methods multiple case codesign study

IntroductionThe WHO has stated that vaccine hesitancy is a serious threat to overcoming COVID-19. Vaccine hesitancy among underserved and at-risk communities is an ongoing challenge in Canada. Public confidence in...

COVID-19 Response Efficacy with Biofarma's Cold Chain Vaccine Distribution System in Indonesia: An Analysis of Technology and Policy Synergy

This study delves into the synergy between technology and policy in Biofarma's Cold Chain Vaccine Distribution System in Indonesia amid the pandemic. This research aims to identify and quantify the tangible and intangible benefits of technology-policy integration, assess the system's influence on the timeliness and quantity of vaccine delivery, and evaluate the maintenance of vaccine quality across Indonesia's diverse regions. Utilizing a qualitative methodology, the study conducted extensive interviews with three representatives from different Indonesian provinces to uncover the impacts of technology and policy integration on vaccine distribution. The results spotlight several key patterns those are 1) Technological Backbone: Data Integration & Distribution: Automation has significantly transformed coordination and precision in vaccine distribution. 2) Operational Revolution: Efficiency & Adaptability: The system has notably enhanced operational efficiency and adaptability. 3) Regional Nuances: System Challenges & Refinements: Identifying unique challenges across various regions shed light on factors impacting the efficacy of the distribution system. 4) Vaccine Safeguarding: Real-time Monitoring & Inventory Transparency: Real-time monitoring and transparent inventory management ensure vaccine quality and reliability. 5)Horizon Scanning: Technological Advancements & Environmental Adaptations: Recommendations for technological advancements and proactive measures to refine vaccine distribution strategies have emerged. Refined and named patterns accurately represent the essence of the data, emphasizing the pivotal role of technology and policy integration in effective vaccine distribution amid the COVID-19 crisis. The study underscores the critical alignment of technology and policy to confront challenges and enhance vaccine distribution, impacting the ongoing response to COVID-19 and future global humanitarian operations.

DECIPHERING DYNAMICS OF COVID-19 OUTBREAK IN INDIA: AN AGE-STRUCTURED MODEL

The dynamics of infectious disease transmission depends on social contact patterns and the precautions people take to minimize disease transmission. The social contact pattern varies depending on the community at large age distribution at work, school, and recreation. Consequently, knowing the age-specific prevalence and incidence of infectious diseases is critical for predicting future disease burden and the efficacy of interventions like vaccination. In this study, we use an SEIR age-structured multi-group epidemic model to understand how social contact affects disease control. We construct location-specific social contact matrices to observe that how social mixing affects disease spread. For mathematical analysis, we compute the basic reproduction number [Formula: see text] and exhibit the global behavior of the system in terms of [Formula: see text]. We also estimate the transmission rate using the empirical data of COVID-19 for India from 1 September 2020, to 31 December 2020. We simulate the lifting of non-pharmaceutical interventions by allowing people to return to work in phases and investigate its impact. Our findings imply that raising awareness in symptomatic infected individuals aged 20–49 years can help in reducing the number of infected individuals. When some schools are partially open, awareness in symptomatic infected individuals in school-age groups also plays a significant role in reducing disease cases. The simulation results also suggest that limiting contact at school and other gathering places could significantly lower the number of instances. Using the least square approach, we show that the time-dependent transmission rate is more realistic than the constant spread rate for COVID-19 in India. To reduce the COVID-19 burden, we obtain that gradually loosening control measures could flatten and lower other peaks. Our findings may help health policymakers to decide on timely age-based vaccination distribution strategies and control measures.

Trends in COVID-19 and influenza vaccine ordering and distribution in Massachusetts jails

Incarcerated populations are highly vulnerable to respiratory illnesses such as COVID-19 and influenza. We evaluated COVID-19 and influenza vaccine ordering and administration rates among 13 of 14 Massachusetts county jails and compared them with rates in the general population. Results showed heterogeneity in the number of vaccines ordered per incarcerated individual across institutions, with small to medium-sized jails ordering more vaccines per person. Vaccine administration in jails utilized approximately 41% of the total vaccines ordered by jails. Additionally, the study revealed disparities in vaccine brand distribution between incarcerated and non-incarcerated populations, potentially perpetuating historical health inequities in carceral settings. Considering that vaccine hesitancy among incarcerated individuals and jail staff has been identified as a significant barrier to vaccination, these findings underscore the need for equitable and comprehensive vaccine distribution strategies in carceral settings, necessitating collaboration between public health and correctional systems to ensure the health and well-being of incarcerated individuals.

Strategies and Trends in COVID-19 Vaccination Delivery: What We Learn and What We May Use for the Future.

Vaccination has been the most effective way to control the outbreak of the COVID-19 pandemic. The numbers and types of vaccines have reached considerable proportions, even if the question of vaccine procedures and frequency still needs to be resolved. We have come to learn the necessity of defining vaccination distribution strategies with regard to COVID-19 that could be used for any future pandemics of similar gravity. In fact, vaccine monitoring implies the existence of a strategy that should be measurable in terms of input and output, based on a mathematical model, including death rates, the spread of infections, symptoms, hospitalization, and so on. This paper addresses the issue of vaccine diffusion and strategies for monitoring the pandemic. It provides a description of the importance and take up of vaccines and the links between procedures and the containment of COVID-19 variants, as well as the long-term effects. Finally, the paper focuses on the global scenario in a world undergoing profound social and political change, with particular attention on current and future health provision. This contribution would represent an example of vaccination experiences, which can be useful in other pandemic or epidemiological contexts.

Does the world need to change its vaccine distribution strategy for COVID-19?

During an emergency, there are many activities in a pharmaceutical supply chain (PSC) which are rendered ineffective. This study aims to propose a holistic approach for Big Data Driven Pharmaceuticals Supply Chain (BDDPSC) during medical emergencies. During unprecedented situations, the quality of healthcare services by using traditional supply chain becomes a challenge. The current study aims to generate a model wherein multiple entities will be the part of data entries like hospitals, clinical trials, medical practitioners, and drug manufacturing companies during COVID-19. The study has considered certified medical practitioners as the experts and based their responses for proposing a theoretical framework deploying E-Delphi–Qualitative Data Analysis approach. By critically examining experts’ responses and comments, the study formulated four major themes and ten sub-themes for smooth functioning of BDDPSCs during an emergency. The E-Delphi was conducted in two rounds to reach final consensus and to find a balance for PSC in terms of efficiency and quality. This research is novel wherein big data enabled PSC theoretical model has been formulated using a qualitative approach for handling COVID-19. The proposed framework provides an enriched way to capture data from the important link viz. “health officials” of PSCs.

Quantifying the benefits of customized vaccination strategies: A network‐based optimization approach

AbstractWe study the problem of designing vaccine distribution strategies that maximally mitigate the negative impact of an infectious disease outbreak. This is achieved through a multiperiod optimization‐based framework that embeds important subject‐specific risk and contact information into the decision‐making process. By analyzing the structure of the resulting optimization problem, we identify key structural properties which we use to construct a globally convergent solution scheme (suitable for smaller problem instances) and two, more scalable, heuristic schemes. We demonstrate the benefits of the considered framework through a case study on COVID‐19 in Texas. Our results highlight the importance of considering risk and contact information as doing so substantially reduces the total expected number of fatalities over conventional compartmental‐based approaches. These findings indicate that customization can have a significant benefit, particularly for community‐scale planning.

Optimal vaccination strategies for COVID-19 in population migration between two regions scenario

ABSTRACT Population movements had a significant impact on the spread of COVID-19, and vaccination is considered the most effective means for humans to face viral infections. This study identifies the optimal control strategy for COVID-19 prevention and control, and explores the impact of short-term and long-term migration on the optimal proportion of vaccine allocation between two regions. We proposed to establish the SIR (Susceptible-Infectious-Recovered) model and determine the stability by calculating the disease free equilibrium and Jacobi matrix of the model. We then established the vaccine optimization model, solved the optimal vaccine distribution strategy by gradient descent method and explored the impact of short-term and long-term migration on the optimal vaccine allocation ratio. The stability analysis revealed that the virus could not be eliminated only by reducing the migration rates and infection rates. we introduced the vaccine methods and obtained the optimal vaccine allocation ratio in Shenzhen and Hong Kong as p 1 : p 2 = 0.000341 : 0.001739 , and the daily vaccination rate we need to impose in each region as p 1 : p 2 = 0.00068 : 0.001901 . The presence or absence of short-term migration had no greater impact on the distribution of the vaccine, whereas R v with long-term migration had a greater effect than no migration. We found that migration rates could not eliminate the outbreak in both regions and that adopting an effective vaccine distribution strategy could be more effective in eliminating the outbreak. And for different allocation scenarios with limited vaccine supply, we obtained the optimal allocation most favorable to control the epidemic.

Vaccines for monkeypox disease and challenges in its production and distribution: a lesson from COVID-19 pandemic.

Vaccines for monkeypox disease and challenges in its production and distribution: a lesson from COVID-19 pandemic.

Impact of the COVID-19 vaccine booster strategy on vaccine protection: a pilot study of a military hospital in Taiwan.

The global fight against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has led to widespread vaccination efforts, yet the optimal dosing schedule for SARS-CoV-2 vaccines remains a subject of ongoing research. This study aims to investigate the effectiveness of administering two booster doses as the third and fourth doses at different intervals to enhance vaccine protection. This study was conducted at a military regional hospital operated by the Ministry of National Defense in Taiwan. A cohort of vaccinated individuals was selected, and their vaccine potency was assessed at various time intervals following their initial vaccine administration. The study participants received booster doses as the third and fourth doses, with differing time intervals between them. The study monitored neutralizing antibody titers and other relevant parameters to assess vaccine efficacy. Our findings revealed that the potency of the SARS-CoV-2 vaccine exhibited a significant decline 80 days after the initial vaccine administration. However, a longer interval of 175 days between booster injections resulted in significantly higher neutralizing antibody titers. The individuals who received the extended interval boosters exhibited a more robust immune response, suggesting that a vaccine schedule with a 175-day interval between injections may provide superior protection against SARS-CoV-2. This study underscores the importance of optimizing vaccine booster dosing schedules to maximize protection against SARS-CoV-2. The results indicate that a longer interval of 175 days between the third and fourth doses of the vaccine can significantly enhance the neutralizing antibody response, potentially offering improved protection against the virus. These findings have important implications for vaccine distribution and administration strategies in the ongoing battle against the SARS-CoV-2 pandemic. Further research and large-scale trials are needed to confirm and extend these findings for broader public health implications.

Politics, Vaccine Distribution, and Public Reception during the Covid-19 Pandemic in Enugu State

The COVID-19 pandemic has posed unprecedented challenges to governments worldwide, with significant implications for public health, social and economic development, and global security. This study aims to examine the politics surrounding the distribution of COVID-19 vaccines and its impact on public reception in Enugu State, Nigeria. Using political ecology theory and a mixed-method approach that includes data collection through interviews, surveys, and document analysis, the study explored the factors that shape the distribution of vaccines and how government officials, community leaders, and public health agencies are involved in the distribution process. Additionally, the study will investigate how the political climate in Enugu State contributes to the public's perception and reception of the vaccine distribution efforts. The study seeks to identify the challenges encountered during the distribution of the COVID-19 vaccines in Enugu, including political influence, corruption, and bureaucratic red tape, among other factors. The study shows that inadequate vaccine distribution has led to elitist vaccine reception. The findings of this study will provide valuable insights to policymakers, public health officials and community leaders on the challenges and opportunities for effective vaccine distribution strategies in Enugu State, contributing to the pandemic response in Nigeria and beyond.

A COVID-19 model incorporating variants, vaccination, waning immunity, and population behavior

Vaccines for COVID-19 have allowed countries to combat the spread of the disease. However, new variants have resulted in significant spikes in cases and raised severe health and economic concerns. We present a COVID-19 model to predict coupled effects of vaccine multiple-dose roll-out strategies, vaccine efficacy, waning immunity, population level of caution, sense of safety, under-reporting of cases, and highly prevalent variants such as the Delta (B.1.617.2) and Omicron (B.1.1.529). The modeling framework can incorporate new variants as they emerge to give critical insights into the new cases and guide public policy decision-making concerning vaccine roll-outs and reopening strategies. The model is shown to recreate the history of COVID-19 for five countries (Germany, India, Japan, South Africa, and the United States). Parameters for crucial aspects of the pandemic, such as population behavior, new variants, vaccination, and waning immunity, can be adjusted to predict pandemic scenarios. The model was used to conduct trend analysis to simulate pandemic dynamics taking into account the societal level of caution, societal sense of safety, and the proportions of individuals vaccinated with first, second, and booster doses. We used the results of serological testing studies to estimate the actual number of cases across countries. The model allows quantification of otherwise hard to quantify aspects such as the infectious power of variants and the effectiveness of government mandates and population behavior. Some example cases are presented by investigating the competitive nature of COVID variants and the effect of different vaccine distribution strategies between immunity groups.

The influence of place on COVID-19 vaccine coverage in Alberta: A multilevel analysis.

While there is evidence of urban/rural disparities in COVID-19 vaccination coverage, there is limited data on the influence of other place-based variables. In this cross-sectional study, we analyzed population-based linked administrative health data (publicly-funded health insurance database and province-wide immunization repository) to examine vaccination coverage for 3,945,103 residents aged 12 years and above in Alberta, Canada. We used multilevel logistic regression to examine the association of vaccination coverage with various place-based variables. Furthermore, we combined information on vaccine coverage and neighborhood level COVID-19 risk to categorize forward sortation areas (FSAs) into six categories. After 4 months of widely available COVID-19 vaccine, coverage varied widely between rural and urban areas (58% to 73%) and between geographic health authority zones (55.8% to 72.8%). Residents living in neighborhoods with lower COVID-19 disease incidence had the lowest vaccination coverage (63.2%), while coverage in higher incidence neighborhoods ranged from 68.3% to 71.9%. The multilevel logistic regression model indicated that residence in metro (adjusted odds ratio [aOR] 1.37; 95% CI: 1.31–1.42) and urban areas (aOR 1.11; 95% CI: 1.08–1.14) was associated with higher vaccine coverage than residence in rural areas. Similarly, residence in Edmonton, Calgary, and South health zones was associated with higher vaccine coverage compared to residence in Central zone. Higher income neighborhoods reported higher vaccine coverage than the lowest-income neighborhoods, and the highest COVID-19 risk neighborhoods reported higher vaccine coverage than the lowest risk neighborhoods (aOR 1.52; 95% CI: 1.12–2.05). In the first four months of wider vaccine availability in Alberta, COVID-19 vaccine coverage varied according to various place-based characteristics. Vaccine distribution strategies need to consider place-based variables for program prioritization and delivery.