Quantifying the impact of social groups and vaccination on inequalities in infectious diseases using a mathematical model.
Ontology highlight
ABSTRACT: Social and cultural disparities in infectious disease burden are caused by systematic differences between communities. Some differences have a direct and proportional impact on disease burden, such as health-seeking behaviour and severity of infection. Other differences-such as contact rates and susceptibility-affect the risk of transmission, where the impact on disease burden is indirect and remains unclear. Furthermore, the concomitant impact of vaccination on such inequalities is not well understood.To quantify the role of differences in transmission on inequalities and the subsequent impact of vaccination, we developed a novel mathematical framework that integrates a mechanistic model of disease transmission with a demographic model of social structure, calibrated to epidemiologic and empirical social contact data.Our model suggests realistic differences in two key factors contributing to the rates of transmission-contact rate and susceptibility-between two social groups can lead to twice the risk of infection in the high-risk population group relative to the low-risk population group. The more isolated the high-risk group, the greater this disease inequality. Vaccination amplified this inequality further: equal vaccine uptake across the two population groups led to up to seven times the risk of infection in the high-risk group. To mitigate these inequalities, the high-risk population group would require disproportionately high vaccination uptake.Our results suggest that differences in contact rate and susceptibility can play an important role in explaining observed inequalities in infectious diseases. Importantly, we demonstrate that, contrary to social policy intentions, promoting an equal vaccine uptake across population groups may magnify inequalities in infectious disease risk.
<h4>Background</h4>Social and cultural disparities in infectious disease burden are caused by systematic differences between communities. Some differences have a direct and proportional impact on disease burden, such as health-seeking behaviour and severity of infection. Other differences-such as contact rates and susceptibility-affect the risk of transmission, where the impact on disease burden is indirect and remains unclear. Furthermore, the concomitant impact of vaccination on such inequalit ...[more]
Project description:Infectious diseases such as malaria, tuberculosis (TB), human immunodeficiency virus (HIV), and the coronavirus disease of 2019 (COVID-19) are problematic globally, with high prevalence particularly in Africa, attributing to most of the death rates. There have been immense efforts toward developing effective preventative and therapeutic strategies for these pathogens globally, however, some remain uncured. Disease susceptibility and progression for malaria, TB, HIV, and COVID-19 vary among individuals and are attributed to precautionary measures, environment, host, and pathogen genetics. While studying individuals with similar attributes, it is suggested that host genetics contributes to most of an individual's susceptibility to disease. Several host genes are identified to associate with these pathogens. Interestingly, many of these genes and polymorphisms are common across diseases. This paper analyzes genes and genetic variations within host genes associated with HIV, TB, malaria, and COVID-19 among different ethnic groups. The differences in host-pathogen interaction among these groups, particularly of Caucasian and African descent, and which gene polymorphisms are prevalent in an African population that possesses protection or risk to disease are reviewed. The information in this review could potentially help develop personalized treatment that could effectively combat the high disease burden in Africa.
Project description:This study introduces an SIRS compartmental mathematical model encompassing vaccination and variable immunity periods for infectious diseases. I derive a basic reproduction number formula and assess the local and global stability of disease-free and the local stability of the endemic equilibria. I demonstrate that the basic reproduction number in the presence of a vaccine is highly sensitive to the rate of immunity loss, and even a slight reduction in this rate can significantly contribute to disease control. Additionally, I have derived a formula to calculate the critical efficacy period required for a vaccine to effectively manage and control the disease.The analysis conducted for the model suggests that increasing the vaccine's immunity duration (efficacy) decelerates disease dynamics, leading to reduced rates of reinfection and less severe disease outcomes. Furthermore, this delay contributes to a decrease in the basic reproduction number ( R0 ), thus facilitating more rapid disease control efforts.
Project description:Fundamental cause theory (FCT) is influential for explaining the enduring relationship between social position and health, yet few empirical studies test FCT's contention that policy supporting the equal distribution of interventions across populations can help reduce health inequalities. Following human papillomavirus (HPV) vaccine approval, complex socioeconomic and racial-ethnic inequalities emerged in distinct stages of the diffusion of this health innovation. Virginia and the District of Columbia were the first U.S. jurisdictions to implement school-entry HPV vaccination mandates for sixth-grade girls, offering an opportunity to test whether inequalities in HPV vaccination are mitigated by policy that seeks to standardize the age of vaccine administration and remove barriers to knowledge about the vaccine. Using data from the 2008, 2009, 2011, 2012, and 2013 National Immunization Survey-Teen (N = 4579) and a triple-difference approach, this study tests whether vaccine mandates are associated with smaller socioeconomic and racial-ethnic inequalities in health provider recommendation and vaccine uptake. It finds mandates were associated with improvements in provider recommendation and vaccine uptake for some socioeconomic and racial-ethnic groups. However, mandates also likely led to a decline in HPV vaccine series completion overall. Implications of these findings for informing FCT and vaccination policy are discussed.
Project description:The development of a successful vaccine, which should elicit a combination of humoral and cellular responses to control or prevent infections, is the first step in protecting against infectious diseases. A vaccine may protect against bacterial, fungal, parasitic, or viral infections in animal models, but to be effective in humans there are some issues that should be considered, such as the adjuvant, the route of vaccination, and the antigen-carrier system. While almost all licensed vaccines are injected such that inoculation is by far the most commonly used method, injection has several potential disadvantages, including pain, cross contamination, needlestick injury, under- or overdosing, and increased cost. It is also problematic for patients from rural areas of developing countries, who must travel to a hospital for vaccine administration. Noninvasive immunizations, including oral, intranasal, and transcutaneous administration of vaccines, can reduce or eliminate pain, reduce the cost of vaccinations, and increase their safety. Several preclinical and clinical studies as well as experience with licensed vaccines have demonstrated that noninvasive vaccine immunization activates cellular and humoral immunity, which protect against pathogen infections. Here we review the development of noninvasive immunization with vaccines based on live attenuated virus, recombinant adenovirus, inactivated virus, viral subunits, virus-like particles, DNA, RNA, and antigen expression in rice in preclinical and clinical studies. We predict that noninvasive vaccine administration will be more widely applied in the clinic in the near future.
Project description:Infectious diseases are a leading cause of morbidity and mortality worldwide with vaccines playing a critical role in preventing deaths. To better understand the impact of low vaccination rates and previous epidemics on infectious disease rates, and how these may help to understand the potential impacts of the current coronavirus disease 2019 (COVID-19) pandemic, a targeted literature review was conducted. Globally, studies suggest past suboptimal vaccine coverage has contributed to infectious disease outbreaks in vulnerable populations. Disruptions caused by the COVID-19 pandemic have contributed to a decline in vaccination uptake and a reduced incidence in several infectious diseases; however, these rates have increased following the lifting of COVID-19 restrictions with modeling studies suggesting a risk of increased morbidity and mortality from several vaccine-preventable diseases. This suggests a window of opportunity to review vaccination and infectious disease control measures before we see further disease resurgence in populations and age-groups currently unaffected.
Project description:Background:Mathematical models are increasingly used to understand the dynamics of infectious diseases, including "chronic" infections with long generation times. Such models include features that are obscure to most clinicians and decision-makers. Methods:Using a model of a hypothetical active case-finding intervention for tuberculosis in India as an example, we illustrate the effects on model results of different choices for model structure, input parameters, and calibration process. Results:Using the same underlying data, different transmission models produced different estimates of the projected intervention impact on tuberculosis incidence by 2030 with different corresponding uncertainty ranges. We illustrate the reasons for these differences and present a simple guide for clinicians and decision-makers to evaluate models of infectious diseases. Conclusions:Mathematical models of chronic infectious diseases must be understood to properly inform policy decisions. Improved communication between modelers and consumers is critical if model results are to improve the health of populations.
Project description:South Asian countries have developed infectious disease control programs such as routine immunization, vaccination, and the provision of essential drugs which are operating nationwide in cooperation with many local and foreign NGOs. Most South Asian countries have a relatively low prevalence of HIV/AIDS until now, but issues like poverty, food insecurity, illiteracy, poor sanitation, and social stigma around AIDS are widespread and are creating formidable challenges to prevention of further spread of this epidemic. Besides that, resurgence of tuberculosis along with the emergence of the drug resistant (MDR-TB and XDRTB) strains and the coepidemic of TB and HIV are posing ever-growing threats to the underdeveloped healthcare infrastructure. The countries are undergoing an epidemiological transition where the disease burden is gradually shifting to noncommunicable diseases, but the infectious diseases still account for almost half of the total disease burden. Despite this huge burden of infectious diseases in South Asia, which is second only to Africa, there is yet any study on the social determinants of infectious diseases in a local context. This paper examines various issues surrounding the social determinants of infectious diseases in South Asian countries with a special reference to HIV and tuberculosis. And, by doing so, it attempts to provide a framework for formulating more efficient prevention and intervention strategies for the future.
Project description:BackgroundHighlighted by the rise of COVID-19, climate change, and conflict, socially vulnerable populations are least resilient to disaster. In infectious disease management, mathematical models are a commonly used tool. Researchers should include social vulnerability in models to strengthen their utility in reflecting real-world dynamics. We conducted a scoping review to evaluate how researchers have incorporated social vulnerability into infectious disease mathematical models.MethodsThe methodology followed the Joanna Briggs Institute and updated Arksey and O'Malley frameworks, verified by the PRISMA-ScR checklist. PubMed, Clarivate Web of Science, Scopus, EBSCO Africa Wide Information, and Cochrane Library were systematically searched for peer-reviewed published articles. Screening and extracting data were done by two independent researchers.ResultsOf 4075 results, 89 articles were identified. Two-thirds of articles used a compartmental model (n = 58, 65.2%), with a quarter using agent-based models (n = 24, 27.0%). Overall, routine indicators, namely age and sex, were among the most frequently used measures (n = 42, 12.3%; n = 22, 6.4%, respectively). Only one measure related to culture and social behaviour (0.3%). For compartmental models, researchers commonly constructed distinct models for each level of a social vulnerability measure and included new parameters or influenced standard parameters in model equations (n = 30, 51.7%). For all agent-based models, characteristics were assigned to hosts (n = 24, 100.0%), with most models including age, contact behaviour, and/or sex (n = 18, 75.0%; n = 14, 53.3%; n = 10, 41.7%, respectively).ConclusionsGiven the importance of equitable and effective infectious disease management, there is potential to further the field. Our findings demonstrate that social vulnerability is not considered holistically. There is a focus on incorporating routine demographic indicators but important cultural and social behaviours that impact health outcomes are excluded. It is crucial to develop models that foreground social vulnerability to not only design more equitable interventions, but also to develop more effective infectious disease control and elimination strategies. Furthermore, this study revealed the lack of transparency around data sources, inconsistent reporting, lack of collaboration with local experts, and limited studies focused on modelling cultural indicators. These challenges are priorities for future research.
Project description:During outbreaks of deadly emerging pathogens (e.g., Ebola, MERS-CoV) and bioterror threats (e.g., smallpox), actively monitoring potentially infected individuals aims to limit disease transmission and morbidity. Guidance issued by CDC on active monitoring was a cornerstone of its response to the West Africa Ebola outbreak. There are limited data on how to balance the costs and performance of this important public health activity. We present a framework that estimates the risks and costs of specific durations of active monitoring for pathogens of significant public health concern. We analyze data from New York City's Ebola active monitoring program over a 16-month period in 2014-2016. For monitored individuals, we identified unique durations of active monitoring that minimize expected costs for those at "low (but not zero) risk" and "some or high risk": 21 and 31 days, respectively. Extending our analysis to smallpox and MERS-CoV, we found that the optimal length of active monitoring relative to the median incubation period was reduced compared to Ebola due to less variable incubation periods. Active monitoring can save lives but is expensive. Resources can be most effectively allocated by using exposure-risk categories to modify the duration or intensity of active monitoring.
Project description:Since the initial use of vaccination in the eighteenth century, our understanding of human and animal immunology has greatly advanced and a wide range of vaccine technologies and delivery systems have been developed. The COVID-19 pandemic response leveraged these innovations to enable rapid development of candidate vaccines within weeks of the viral genetic sequence being made available. The development of vaccines to tackle emerging infectious diseases is a priority for the World Health Organization and other global entities. More than 70% of emerging infectious diseases are acquired from animals, with some causing illness and death in both humans and the respective animal host. Yet the study of critical host-pathogen interactions and the underlying immune mechanisms to inform the development of vaccines for their control is traditionally done in medical and veterinary immunology 'silos'. In this Perspective, we highlight a 'One Health vaccinology' approach and discuss some key areas of synergy in human and veterinary vaccinology that could be exploited to accelerate the development of effective vaccines against these shared health threats.
