Potential for rabies control through dog vaccination in wildlife-abundant communities of Tanzania

Canine vaccination has been successful in controlling rabies in diverse settings worldwide. However, concerns remain that coverage levels which have previously been sufficient might be insufficient in systems where transmission occurs both between and within populations of domestic dogs and other carnivores. To evaluate the effectiveness of vaccination targeted at domestic dogs when wildlife also contributes to transmission, we applied a next-generation matrix model based on contract tracing data from the Ngorongoro and Serengeti Districts in northwest Tanzania. We calculated corresponding values of R0, and determined, for policy purposes, the probabilities that various annual vaccination targets would control the disease, taking into account the empirical uncertainty in our field data. We found that transition rate estimates and corresponding probabilities of vaccination-based control indicate that rabies transmission in this region is driven by transmission within domestic dogs. Different patterns of rabies transmission between the two districts exist, with wildlife playing a more important part in Ngorongoro and leading to higher recommended coverage levels in that district. Nonetheless, our findings indicate that an annual dog vaccination campaign achieving the WHO-recommended target of 70% will control rabies in both districts with a high level of certainty. Our results support the feasibility of controlling rabies in Tanzania through dog vaccination

Projecting hospital utilization during the COVID-19 outbreaks in the United States

Data deposition: The computational system is available in Github (https://github.com/affans/ncov2019odemodel).In the wake of community coronavirus disease 2019 (COVID-19) transmission in the United States, there is a growing public health concern regarding the adequacy of resources to treat infected cases. Hospital beds, intensive care units (ICUs), and ventilators are vital for the treatment of patients with severe illness. To project the timing of the outbreak peak and the number of ICU beds required at peak, we simulated a COVID-19 outbreak parameterized with the US population demographics. In scenario analyses, we varied the delay from symptom onset to self-isolation, the proportion of symptomatic individuals practicing self-isolation, and the basic reproduction number R0. Without self-isolation, when R0 =2.5, treatment of critically ill individuals at the outbreak peak would require 3.8 times more ICU beds than exist in the United States. Self-isolation by 20% of cases 24 h after symptom onset would delay and flatten the outbreak trajectory, reducing the number of ICU beds needed at the peak by 48.4% (interquartile range 46.4-50.3%), although still exceeding existing capacity. When R0 =2, twice as many ICU beds would be required at the peak of outbreak in the absence of self-isolation. In this scenario, the proportional impact of self-isolation within 24 h on reducing the peak number of ICU beds is substantially higher at 73.5% (interquartile range 71.4-75.3%). Our estimates underscore the inadequacy of critical care capacity to handle the burgeoning outbreak. Policies that encourage self-isolation, such as paid sick leave, may delay the epidemic peak, giving a window of time that could facilitate emergency mobilization to expand hospital capacity.S.M.M. acknowledges support from the Canadian Institutes of Health Research (grant OV4-170643; Canadian 2019 Novel Coronavirus Rapid Research), and the Natural Sciences and Engineering Research Council of Canada. A.P.G. gratefully acknowledges funding from the NIH (grant UO1-GM087719), the Burnett and Stender families’ endowment, the Notsew Orm Sands Foundation, NIH grant 1R01AI151176-01, and National Science Foundation grant RAPID-2027755. M.C.F. was supported by the NIH grant K01 AI141576.Integrative Biolog

The impact of vaccination on COVID-19 Outbreaks in the United States

Background: Global vaccine development efforts have been accelerated in response to the devastating COVID-19 pandemic. We evaluated the impact of a 2-dose COVID-19 vaccination campaign on reducing incidence, hospitalizations, and deaths in the United States (US). Methods: We developed an agent-based model of SARS-CoV-2 transmission and parameterized it with US demographics and age-specific COVID-19 outcomes. Healthcare workers and high-risk individuals were prioritized for vaccination, while children under 18 years of age were not vaccinated. We considered a vaccine efficacy of 95% against disease following 2 doses administered 21 days apart achieving 40% vaccine coverage of the overall population within 284 days. We varied vaccine efficacy against infection, and specified 10% pre-existing population immunity for the base-case scenario. The model was calibrated to an effective reproduction number of 1.2, accounting for current non-pharmaceutical interventions in the US. Results: Vaccination reduced the overall attack rate to 4.6% (95% CrI: 4.3% - 5.0%) from 9.0% (95% CrI: 8.4% - 9.4%) without vaccination, over 300 days. The highest relative reduction (54-62%) was observed among individuals aged 65 and older. Vaccination markedly reduced adverse outcomes, with non-ICU hospitalizations, ICU hospitalizations, and deaths decreasing by 63.5% (95% CrI: 60.3% - 66.7%), 65.6% (95% CrI: 62.2% - 68.6%), and 69.3% (95% CrI: 65.5% - 73.1%), respectively, across the same period. Conclusions: Our results indicate that vaccination can have a substantial impact on mitigating COVID-19 outbreaks, even with limited protection against infection. However, continued compliance with non-pharmaceutical interventions is essential to achieve this impact.Integrative Biolog

Cost-effective proactive testing strategies during COVID-19 mass vaccination: A modelling study

Background: As SARS-CoV-2 vaccines are administered worldwide, the COVID-19 pandemic continues to exact significant human and economic costs. Mass testing of unvaccinated individuals followed by isolation of positive cases can substantially mitigate risks and be tailored to local epidemiological conditions to ensure cost effectiveness. Methods: Using a multi-scale model that incorporates population-level SARS-CoV-2 transmission and individual-level viral load kinetics, we identify the optimal frequency of proactive SARS-CoV-2 testing, depending on the local transmission rate and proportion immunized. Findings: Assuming a willingness-to-pay of US$100,000 per averted year of life lost (YLL) and a price of$10 per test, the optimal strategy under a rapid transmission scenario (Re ~ 2.5) is daily testing until one third of the population is immunized and then weekly testing until half the population is immunized, combined with a 10-day isolation period of positive cases and their households. Under a low transmission scenario (Re ~ 1.2), the optimal sequence is weekly testing until the population reaches 10% partial immunity, followed by monthly testing until 20% partial immunity, and no testing thereafter. Interpretation: Mass proactive testing and case isolation is a cost effective strategy for mitigating the COVID-19 pandemic in the initial stages of the global SARS-CoV-2 vaccination campaign and in response to resurgences of vaccine-evasive variants.US National Institutes of Health, US Centers for Disease Control and Prevention, HK Innovation and Technology Commission, China National Natural Science Foundation, European Research Council, and EPSRC Impact Acceleration Grant.Integrative Biolog

Cost-effectiveness of next-generation vaccines: The case of pertussis.

Despite steady vaccination coverage rates, pertussis incidence in the United States has continued to rise. This public health challenge has motivated calls for the development of a new vaccine with greater efficacy and duration of protection. Any next-generation vaccine would likely come at a higher cost, and must provide sufficient health benefits beyond those provided by the current vaccine in order to be deemed cost-effective. Using an age-structured transmission model of pertussis, we quantified the health and economic benefits of a next-generation vaccine that would enhance either the efficacy or duration of protection of the childhood series, the duration of the adult booster, or a combination. We developed a metric, the maximum cost-effective price increase (MCPI), to compare the potential value of such improvements. The MCPI estimates the per-dose price increase that would maintain the cost-effectiveness of pertussis vaccination. We evaluated the MCPI across a range of potential single and combined improvements to the pertussis vaccine. As an upper bound, we found that a next-generation vaccine which could achieve perfect efficacy for the childhood series would permit an MCPI of $18 per dose (95$12-$31). Pertussis vaccine improvements that extend the duration of protection to an average of 75 years would allow for an MCPI of$22 per dose for the childhood series (CI: $10-$33) or $12 for the adult booster (CI:$4-$18). Despite the short duration of the adult booster, improvements to the childhood series could be more valuable than improvements to the adult booster. Combining improvements in both efficacy and duration, a childhood series with perfect efficacy and average duration of 75 years would permit an MCPI of$39 per dose, the highest of any scenario evaluated. Our results highlight the utility of the MCPI metric in evaluating potential vaccines or other interventions when prices are unknown

Impact of One-Health framework on vaccination cost-effectiveness : a case study of rabies in Ethiopia

Livestock losses due to rabies and health and the corresponding benefits of controlling the disease are not often considered when the cost-effectiveness of rabies control is evaluated. In this research, assessed the benefits of applying a One Health perspective that includes these losses to the case of canine rabies vaccination in Ethiopia. We constructed a dynamic epidemiological model of rabies transmission. The model was fit to district-specific data on human rabies exposures and canine demography for two districts with distinct agro-ecologies. The epidemiological model was coupled with human and livestock economic outcomes to predict the health and economic impacts under a range of vaccination scenarios. The model indicates that human exposures, human deaths, and rabies-related livestock losses would decrease monotonically with increasing vaccination coverage. In the rural district, all vaccination scenarios were found to be cost-saving compared to the status quo of no vaccination, as more money could be saved by preventing livestock losses than would be required to fund the vaccination campaigns. Vaccination coverages of 70% and 80% were identified as most likely to provide the greatest net health benefits at the WHO cost-effectiveness threshold over a period of 5 years, in urban and rural districts respectively. Shorter time frames led to recommendations for higher coverage in both districts, as did even a minor threat of rabies re-introduction. Exclusion of rabies-related livestock losses reduced the optimal vaccination coverage for the rural district to 50%. This study demonstrated the importance of including all economic consequences of zoonotic disease into control decisions. Analyses that include cattle and other rabies-susceptible livestock are likely better suited to many rural communities in Africa wishing to maximize the benefits of canine vaccination

Model-based assessment of public health impact and cost-effectiveness of dengue vaccination following screening for prior exposure.

The tetravalent dengue vaccine CYD-TDV (Dengvaxia) is the first licensed vaccine against dengue, but recent findings indicate an elevated risk of severe disease among vaccinees without prior dengue virus (DENV) exposure. The World Health Organization currently recommends CYD-TDV only for individuals with serological confirmation of past DENV exposure. Our objective was to evaluate the potential health impact and cost-effectiveness of vaccination following serological screening. To do so, we used an agent-based model to simulate DENV transmission with and without vaccination over a 10-year timeframe. Across a range of values for the proportion of vaccinees with prior DENV exposure, we projected the proportion of symptomatic and hospitalized cases averted as a function of the sensitivity and specificity of serological screening. Scenarios about the cost-effectiveness of screening and vaccination were chosen to be representative of Brazil and the Philippines. We found that public health impact depended primarily on sensitivity in high-transmission settings and on specificity in low-transmission settings. Cost-effectiveness could be achievable from the perspective of a public payer provided that sensitivity and the value of a disability-adjusted life-year were both high, but only in high-transmission settings. Requirements for reducing relative risk and achieving cost-effectiveness from an individual perspective were more restricted, due to the fact that those who test negative pay for screening but receive no benefit. Our results predict that cost-effectiveness could be achieved only in high-transmission areas of dengue-endemic countries with a relatively high per capita GDP, such as Panamá (13,680 USD), Brazil (8,649 USD), México (8,201 USD), or Thailand (5,807 USD). In conclusion, vaccination with CYD-TDV following serological screening could have a positive impact in some high-transmission settings, provided that screening is highly specific (to minimize individual harm), at least moderately sensitive (to maximize population benefit), and sufficiently inexpensive (depending on the setting)

A Cost-Effectiveness Tool for Informing Policies on Zika Virus Control

Background: As Zika virus continues to spread, decisions regarding resource allocations to control the outbreak underscore the need for a tool to weigh policies according to their cost and the health burden they could avert. For example, to combat the current Zika outbreak the US President requested the allocation of $1.8 billion from Congress in February 2016. Methodology/Principal Findings: Illustrated through an interactive tool, we evaluated how the number of Zika cases averted, the period during pregnancy in which Zika infection poses a risk of microcephaly, and probabilities of microcephaly and Guillain-Barré Syndrome (GBS) impact the cost at which an intervention is cost-effective. From Northeast Brazilian microcephaly incidence data, we estimated the probability of microcephaly in infants born to Zika-infected women (0.49$91,102 and $28,818, respectively. We demonstrated the utility of our cost-effectiveness tool with examples evaluating funding commitments by Costa Rica and Brazil, the US presidential proposal, and the novel approach of genetically modified mosquitoes. Our analyses indicate that the commitments and the proposal are likely to be cost-effective, whereas the cost-effectiveness of genetically modified mosquitoes depends on the country of implementation. Conclusions/Significance: Current estimates from our tool suggest that the health burden from microcephaly and GBS warrants substantial expenditures focused on Zika virus control. Our results justify the funding committed in Costa Rica and Brazil and many aspects of the budget outlined in the US president’s proposal. As data continue to be collected, new parameter estimates can be customized in real-time within our user-friendly tool to provide updated estimates on cost-effectiveness of interventions and inform policy decisions in country-specific settings

Segmental Duplication Implicated in the Genesis of Inversion 2Rj of Anopheles gambiae

The malaria vector Anopheles gambiae maintains high levels of inversion polymorphism that facilitate its exploitation of diverse ecological settings across tropical Africa. Molecular characterization of inversion breakpoints is a first step toward understanding the processes that generate and maintain inversions. Here we focused on inversion 2Rj because of its association with the assortatively mating Bamako chromosomal form of An. gambiae, whose distinctive breeding sites are rock pools beside the Niger River in Mali and Guinea. Sequence and computational analysis of 2Rj revealed the same 14.6 kb insertion between both breakpoints, which occurred near but not within predicted genes. Each insertion consists of 5.3 kb terminal inverted repeat arms separated by a 4 kb spacer. The insertions lack coding capacity, and are comprised of degraded remnants of repetitive sequences including class I and II transposable elements. Because of their large size and patchwork composition, and as no other instances of these insertions were identified in the An. gambiae genome, they do not appear to be transposable elements. The 14.6 kb modules inserted at both 2Rj breakpoint junctions represent low copy repeats (LCRs, also called segmental duplications) that are strongly implicated in the recent (∼0.4Ne generations) origin of 2Rj. The LCRs contribute to further genome instability, as demonstrated by an imprecise excision event at the proximal breakpoint of 2Rj in field isolates

Modelling microbial infection to address global health challenges

The continued growth of the world’s population and increased interconnectivity heighten the risk that infectious diseases pose for human health worldwide. Epidemiological modelling is a tool that can be used to mitigate this risk by predicting disease spread or quantifying the impact of different intervention strategies on disease transmission dynamics. We illustrate how four decades of methodological advances and improved data quality have facilitated the contribution of modelling to address global health challenges, exemplified by models for the HIV crisis, emerging pathogens and pandemic preparedness. Throughout, we discuss the importance of designing a model that is appropriate to the research question and the available data. We highlight pitfalls that can arise in model development, validation and interpretation. Close collaboration between empiricists and modellers continues to improve the accuracy of predictions and the optimization of models for public health decision-making