Vaccination Programs for Endemic Infections: Modelling Real versus Apparent Impacts of Vaccine and Infection Characteristics

Optimal vaccination strategies for imperfect vaccines and variable host susceptibility

I present a method to allocate a given number of vaccines to members of a population who differ in their susceptibility to the disease so that the final size of the epidemic is minimised. I consider an arbitrary distribution of protection that the vaccine confers, including the extreme cases of leaky and all-or-none vaccines. The optimal vaccination policy depends on the distribution of protection. While for low values of the basic reproduction number R0 the optimal policy prioritises the most susceptible hosts, I show that for almost any distribution the order of priority reverses and the least susceptible hosts should be vaccinated when R0 is high. The exception where this does not happen is the all-or-none vaccine. However, even a small deviation from the ideal all-or-none distribution can imply that the limited number of vaccines should be given to less susceptible hosts already at realistic values of R0.

S. Systems and computational analysis of gene expression datasets reveals GRB-2 suppression as an acute immunomodulatory response against enteric infections in endemic settings

Introduction

Enteric infections are a major cause of under-5 (age) mortality in low/middle-income countries. Although vaccines against these infections have already been licensed, unwavering efforts are required to boost suboptimalefficacy and effectiveness in regions that are highly endemic to enteric pathogens. The role of baseline immunological profiles in influencing vaccine-induced immune responses is increasingly becoming clearer for several vaccines. Hence, for the development of advanced and region-specific enteric vaccines, insights into differences in immune responses to perturbations in endemic and non-endemic settings become crucial.

Materials and methods

For this reason, we employed a two-tiered system and computational pipeline (i) to study the variations in differentially expressed genes (DEGs) associated with immune responses to enteric infections in endemic and non-endemic study groups, and (ii) to derive features (genes) of importance that keenly distinguish between these two groups using unsupervised machine learning algorithms on an aggregated gene expression dataset. The derived genes were further curated using topological analysis of the constructed STRING networks. The findings from these two tiers are validated using multilayer perceptron classifier and were further explored using correlation and regression analysis for the retrieval of associated gene regulatory modules.

Results

Our analysis reveals aggressive suppression of GRB-2, an adaptor molecule integral for TCR signaling, as a primary immunomodulatory response against S. typhi infection in endemic settings. Moreover, using retrieved correlation modules and multivariant regression models, we found a positive association between regulators of activated T cells and mediators of Hedgehog signaling in the endemic population, which indicates the initiation of an effector (involving differentiation and homing) rather than an inductive response upon infection. On further exploration, we found STAT3 to be instrumental in designating T-cell functions upon early responses to enteric infections in endemic settings.

Conclusion

Overall, through a systems and computational biology approach, we characterized distinct molecular players involved in immune responses to enteric infections in endemic settings in the process, contributing to the mounting evidence of endemicity being a major determiner of pathogen/vaccine-induced immune responses. The gained insights will have important implications in the design and development of region/endemicity-specific vaccines.

Individual variation in vaccine immune response can produce bimodal distributions of protection

The ability for vaccines to protect against infectious diseases varies among individuals, but computational models employed to inform policy typically do not account for this variation. Here we examine this issue: we implement a model of vaccine efficacy developed in the context of SARS-CoV-2 in order to evaluate the general implications of modelling correlates of protection on the individual level. Due to high levels of variation in immune response, the distributions of individual-level protection emerging from this model tend to be highly dispersed, and are often bimodal. We describe the specification of the model, provide an intuitive parameterisation, and comment on its general robustness. We show that the model can be viewed as an intermediate between the typical approaches that consider the mode of vaccine action to be either "all-or-nothing" or "leaky". Our view based on this analysis is that individual variation in correlates of protection is an important consideration that may be crucial to designing and implementing models for estimating population-level impacts of vaccination programs.

Modelling the impact of perfect and imperfect vaccination strategy against SARS CoV-2 by assuming varied vaccine efficacy over India

Background

The outbreak of Coronavirus disease (COVID-19) has swiftly spread globally and caused public health and socio-economic disruption in many countries. An epidemiological modelling studies in the susceptible-infectious-removed (SIR) has played an important role for making effective public health policy to mitigate the spread of COVID-19. The aim of the present study is to investigate the optimal vaccination strategy to control the COVID-19 pandemic in India.

Methods

We have applied compartment mathematical model susceptible-vaccination-infectious-removed (SVIR) with different range of vaccine efficacy scenarios and predicted the population to be covered for vaccination per day in India as well as state level was performed.

Results

The model assumed that a vaccine has 100% efficacy, predicted that >5 million populace to be vaccinated per day to flatten the epidemic curve in India. Similarly, different vaccination mechanisms such as ‘all-or-nothing’ (AoN) and leaky vaccines does not have potential discordance in their effectiveness at higher efficacies (>70%). However, AoN vaccine was found to be marginally effective than leaky at lower efficacies (<70%) when administered at the higher coverage strategies. Further state level analyses were performed and it was found that 0.3, 0.3, 0.2 and 1 million vaccinations required per day in Andhra Pradesh, Gujarat, Kerala and Maharashtra as it assumes that the vaccine efficacy is 70%.

Conclusion

The proposed modelling approach shows a range of assumptions on the efficacy of vaccine which helps the health authorities to prioritize the vaccination strategies to prevent the transmission as well as disease.

A Review of COVID-19 Modelling Strategies in Three Countries to Develop a Research Framework for Regional Areas

At the end of December 2019, an outbreak of COVID-19 occurred in Wuhan city, China. Modelling plays a crucial role in developing a strategy to prevent a disease outbreak from spreading around the globe. Models have contributed to the perspicacity of epidemiological variations between and within nations and the planning of desired control strategies. In this paper, a literature review was conducted to summarise knowledge about COVID-19 disease modelling in three countries-China, the UK and Australia-to develop a robust research framework for the regional areas that are urban and rural health districts of New South Wales, Australia. In different aspects of modelling, summarising disease and intervention strategies can help policymakers control the outbreak of COVID-19 and may motivate modelling disease-related research at a finer level of regional geospatial scales in the future.

Potential impact of tuberculosis vaccines in China, South Africa, and India

More effective tuberculosis vaccines are needed to help reach World Health Organization tuberculosis elimination goals. Insufficient evidence exists on the potential impact of future tuberculosis vaccines with varying characteristics and in different epidemiological settings. To inform vaccine development decision making, we modeled the impact of hypothetical tuberculosis vaccines in three high-burden countries. We calibrated Mycobacterium tuberculosis (M.tb) transmission models to age-stratified demographic and epidemiological data from China, South Africa, and India. We varied vaccine efficacy to prevent infection or disease, effective in persons M.tb uninfected or infected, and duration of protection. We modeled routine early-adolescent vaccination and 10-yearly mass campaigns from 2025. We estimated median percentage population-level tuberculosis incidence rate reduction (IRR) in 2050 compared to a no new vaccine scenario. In all settings, results suggested vaccines preventing disease in M.tb-infected populations would have greatest impact by 2050 (10-year, 70% efficacy against disease, IRR 51%, 52%, and 54% in China, South Africa, and India, respectively). Vaccines preventing reinfection delivered lower potential impact (IRR 1, 12, and 17%). Intermediate impact was predicted for vaccines effective only in uninfected populations, if preventing infection (IRR 21, 37, and 50%) or disease (IRR 19, 36, and 51%), with greater impact in higher-transmission settings. Tuberculosis vaccines have the potential to deliver substantial population-level impact. For prioritizing impact by 2050, vaccine development should focus on preventing disease in M.tb-infected populations. Preventing infection or disease in uninfected populations may be useful in higher transmission settings. As vaccine impact depended on epidemiology, different development strategies may be required.

Role of modelling in COVID-19 policy development

Models have played an important role in policy development to address the COVID-19 outbreak from its emergence in China to the current global pandemic. Early projections of international spread influenced travel restrictions and border closures. Model projections based on the virus's infectiousness demonstrated its pandemic potential, which guided the global response to and prepared countries for increases in hospitalisations and deaths. Tracking the impact of distancing and movement policies and behaviour changes has been critical in evaluating these decisions. Models have provided insights into the epidemiological differences between higher and lower income countries, as well as vulnerable population groups within countries to help design fit-for-purpose policies. Economic evaluation and policies have combined epidemic models and traditional economic models to address the economic consequences of COVID-19, which have informed policy calls for easing restrictions. Social contact and mobility models have allowed evaluation of the pathways to safely relax mobility restrictions and distancing measures. Finally, models can consider future end-game scenarios, including how suppression can be achieved and the impact of different vaccination strategies.

Age-targeted tuberculosis vaccination in China and implications for vaccine development: a modelling study

BACKGROUND

Tuberculosis is the leading single-pathogen cause of death worldwide, and China has the third largest number of cases worldwide. New tools, such as new vaccines, are needed to meet WHO tuberculosis goals. Tuberculosis vaccine development strategies mostly target infants or adolescents, but given China's ageing epidemic, vaccinating older people might be important. We modelled the potential impact of new tuberculosis vaccines in China targeting adolescents (15-19 years) or older adults (60-64 years) with varying vaccine characteristics to inform strategic vaccine development.

METHODS

A Mycobacterium tuberculosis transmission model was calibrated to age-stratified demographic and epidemiological data from China. Varying scenarios of vaccine implementation (age targeting [adolescents or older adults] and coverage [30% or 70%]) and characteristics (efficacy [40%, 60%, or 80%], duration of protection [10 years or 20 years], and host infection status required for efficacy [pre-infection, post-infection in latency, post-infection in latency or recovered, or pre-infection and post-infection]) were assessed. Primary outcomes were tuberculosis incidence and mortality rate reduction in 2050 in each vaccine scenario compared with the baseline (no new vaccine) scenario and cumulative number needed to vaccinate (NNV) per case or death averted, 2025-50.

FINDINGS

By 2050, results suggest that 74·5% (uncertainty interval [UI] 70·2-78·6) of incident tuberculosis cases in China would occur in people aged 65 years or older, and 75·1% (66·8-80·7) of all cases would be due to reactivation, rather than new infection. All vaccine profiles delivered to older adults had higher population-level impact (reduction of incidence and mortality rates) and lower NNV per case and per death averted than if delivered to adolescents. For an intermediate vaccine scenario of 60% efficacy, 10-year protection, and 70% coverage, the reduction of tuberculosis incidence rates with older adult vaccination was 1·9 times (UI 1·5-2·6) to 157·5 times (119·3-225·6) greater than with adolescent vaccination, and the NNV was 0·011 times (0·008-0·014) to 0·796 times (0·632-0·970) lower. Furthermore, with older adult vaccination, post-infection vaccines provided substantially greater mortality and incidence rate reductions than pre-infection vaccines.

INTERPRETATION

Adolescent-targeted tuberculosis vaccines, the focus of many development plans, would have only a small impact in ageing, reactivation-driven epidemics such as those in China. Instead, an efficacious post-infection vaccine delivered to older adults will be crucial to maximise population-level impact in this setting and would provide an important contribution towards achieving WHO goals. Older adults should be included in tuberculosis vaccine clinical development and implementation planning.

FUNDING

Aeras and UK MRC.

The influence of incomplete case ascertainment on measures of vaccine efficacy

BACKGROUND

Motivated by the unexplained variation in the performance of some vaccines across different settings, we extend previous theoretical work to consider the potential impact of incomplete case ascertainment on measures of vaccine efficacy (VE), which is more likely in subclinical or clinically unimportant infections, such as rotavirus gastroenteritis.

METHODS

By simulating the measurement of VE under outbreak conditions using a discrete time stochastic SIR model, we compare three commonly used measures, VE_Risk, VE_Rate, and VE_Hazard, calculated respectively based on risk ratio, rate ratio and hazard ratio of disease. We investigate how these measures are influenced by factors such as biological activity, action mechanism of vaccine, proportion of cases ascertained, and underlying force of infection.

RESULTS

Under plausibly low levels of ascertainment, the group with the most infections, and therefore the most missed cases, has the most falsely inflated denominator, producing similar rates in the control and intervention groups. As a result, VE_Rate and VE_Hazard will underestimate the true VE compared to high case ascertainment scenarios. Furthermore, the extent of underestimation is greater for leaky vaccine models with lower biological protective effects and under conditions which are conducive to high transmission.

CONCLUSIONS

This study demonstrates that a biologically active vaccine may produce a low measured VE under a range of epidemiological, vaccine-related and logistical conditions. Low case ascertainment may partly explain the observed heterogeneity in the performance of rotavirus vaccine across different settings, and should be considered in the design and interpretation of future field trials.

Modular programming for tuberculosis control, the "AuTuMN" platform

BACKGROUND

Tuberculosis (TB) is now the world's leading infectious killer and major programmatic advances will be needed if we are to meet the ambitious new End TB Targets. Although mathematical models are powerful tools for TB control, such models must be flexible enough to capture the complexity and heterogeneity of the global TB epidemic. This includes simulating a disease that affects age groups and other risk groups differently, has varying levels of infectiousness depending upon the organ involved and varying outcomes from treatment depending on the drug resistance pattern of the infecting strain.

RESULTS

We adopted sound basic principles of software engineering to develop a modular software platform for simulation of TB control interventions ("AuTuMN"). These included object-oriented programming, logical linkage between modules and consistency of code syntax and variable naming. The underlying transmission dynamic model incorporates optional stratification by age, risk group, strain and organ involvement, while our approach to simulating time-variant programmatic parameters better captures the historical progression of the epidemic. An economic model is overlaid upon this epidemiological model which facilitates comparison between new and existing technologies. A "Model runner" module allows for predictions of future disease burden trajectories under alternative scenario situations, as well as uncertainty, automatic calibration, cost-effectiveness and optimisation. The model has now been used to guide TB control strategies across a range of settings and countries, with our modular approach enabling repeated application of the tool without the need for extensive modification for each application.

CONCLUSIONS

The modular construction of the platform minimises errors, enhances readability and collaboration between multiple programmers and enables rapid adaptation to answer questions in a broad range of contexts without the need for extensive re-programming. Such features are particularly important in simulating an epidemic as complex and diverse as TB.

Porcine Circovirus Type 2 (PCV2) Vaccines in the Context of Current Molecular Epidemiology

Porcine circovirus type 2 (PCV2) is an economically important swine pathogen and, although small, it has the highest evolution rate among DNA viruses. Since the discovery of PCV2 in the late 1990s, this minimalistic virus with a 1.7 kb single-stranded DNA genome and two indispensable genes has become one of the most important porcine pathogens, and presently is subjected to the highest volume of prophylactic intervention in the form of vaccines in global swine production. PCV2 can currently be divided into five different genotypes, PCV2a through PCV2e. It is well documented that PCV2 continues to evolve, which is reflected by changes in the prevalence of genotypes. During 2006, commercial vaccines for PCV2 were introduced on a large scale in a pig population mainly infected with PCV2b. Since 2012, the PCV2d genotype has essentially replaced the previously predominant PCV2b genotype in North America and similar trends are also documented in other geographic regions such as China and South Korea. This is the second major PCV2 genotype shift since the discovery of the virus. The potential increase in virulence of the emergent PCV2 genotype and the efficacy of the current vaccines derived from PCV2a genotype against the PCV2d genotype viruses has received considerable attention. This review attempts to synthesize the understanding of PCV2 biology, experimental studies on the antigenic variability, and molecular epidemiological analysis of the evolution of PCV2 genotypes.

Modelling the effect of short-course multidrug-resistant tuberculosis treatment in Karakalpakstan, Uzbekistan

BACKGROUND

Multidrug-resistant tuberculosis (MDR-TB) is a major threat to global TB control. MDR-TB treatment regimens typically have a high pill burden, last 20 months or more and often lead to unsatisfactory outcomes. A 9-11 month regimen with seven antibiotics has shown high success rates among selected MDR-TB patients in different settings and is conditionally recommended by the World Health Organization.

METHODS

We construct a transmission-dynamic model of TB to estimate the likely impact of a shorter MDR-TB regimen when applied in a low HIV prevalence region of Uzbekistan (Karakalpakstan) with high rates of drug resistance, good access to diagnostics and a well-established community-based MDR-TB treatment programme providing treatment to around 400 patients. The model incorporates acquisition of additional drug resistance and incorrect regimen assignment. It is calibrated to local epidemiology and used to compare the impact of shorter treatment against four alternative programmatic interventions.

RESULTS

Based on empirical outcomes among MDR-TB patients and assuming no improvement in treatment success rates, the shorter regimen reduced MDR-TB incidence from 15.2 to 9.7 cases per 100,000 population per year and MDR-TB mortality from 3.0 to 1.7 deaths per 100,000 per year, achieving comparable or greater gains than the alternative interventions. No significant increase in the burden of higher levels of resistance was predicted. Effects are probably conservative given that the regimen is likely to improve success rates.

CONCLUSIONS

In addition to benefits to individual patients, we find that shorter MDR-TB treatment regimens also have the potential to reduce transmission of resistant strains. These findings are in the epidemiological setting of treatment availability being an important bottleneck due to high numbers of patients being eligible for treatment, and may differ in other contexts. The high proportion of MDR-TB with additional antibiotic resistance simulated was not exacerbated by programmatic responses and greater gains may be possible in contexts where the regimen is more widely applicable.

Childhood Vaccination: Implications for Global and Domestic Public Health

The role of vaccination in the control and prevention of endemic and emerging diseases cannot be overemphasized. Induction of host protective immunity may be the most powerful tool and effective strategy in preventing the spread of potentially fatal disease and emerging illnesses, in particular in susceptible immunologically naive hosts. The strategy for vaccination programs is engrained in population studies recognizing benefit for the health and economic welfare of at-risk indigenous populations. Worldwide collaboration is a necessary aspect of vaccine-preventable diseases recognizing that even a small number of wild-type cases of an eradicated disease in one region presents opportunities for re-emergence of the disease in geographically remote areas.

Lessening the Impacts from Non-Tectonic (Natural) Hazards and Triggered Events

Floods are a global problem. They are predictable to some degree by weather forecasting but to a greater degree and with more accuracy when drainage basin monitoring equipment is in place. This includes stream gauges that telemeter the elevation of stream/river surface in a channel and the rate of water flow to a central computing station. The computed data from the telemetered sites plus the input of stream/river channel cross-sections data allow prediction of where flooding will be a problem, when the flooding will reach an area, and to what level out of a channel (magnitude) the flood is estimated to reach. This gives the populations at risk of the flooding early warnings (hours, days) and time to prepare for the floodwaters or to gather important documents and evacuate to safe higher ground.