A computationally efficient method for probabilistic parameter threshold analysis for health economic evaluations

Background. Threshold analysis is used to determine the threshold value of an input parameter at which a health care strategy becomes cost-effective. Typically, it is performed in a deterministic manner, in which inputs are varied one at a time while the remaining inputs are each fixed at their mean value. This approach will result in incorrect threshold values if the cost-effectiveness model is nonlinear or if inputs are correlated. Objective. To propose a probabilistic method for performing threshold analysis, which accounts for the joint uncertainty in all input parameters and makes no assumption about the linearity of the cost-effectiveness model. Methods. Three methods are compared: 1) deterministic threshold analysis (DTA); 2) a 2-level Monte Carlo approach, which is considered the gold standard; and 3) a regression-based method using a generalized additive model (GAM), which identifies threshold values directly from a probabilistic sensitivity analysis sample. Results. We applied the 3 methods to estimate the minimum probability of hospitalization for typhoid fever at which 3 different vaccination strategies become cost-effective in Uganda. The threshold probability of hospitalization at which routine vaccination at 9 months with catchup campaign to 5 years becomes cost-effective is estimated to be 0.060 and 0.061 (95% confidence interval [CI], 0.058–0.064), respectively, for 2-level and GAM. According to DTA, routine vaccination at 9 months with catchup campaign to 5 years would never become cost-effective. The threshold probability at which routine vaccination at 9 months with catchup campaign to 15 years becomes cost-effective is estimated to be 0.092 (DTA), 0.074 (2-level), and 0.072 (95% CI, 0.069–0.075) (GAM). GAM is 430 times faster than the 2-level approach. Conclusions. When the cost-effectiveness model is nonlinear, GAM provides similar threshold values to the 2-level Monte Carlo approach and is computationally more efficient. DTA provides incorrect results and should not be used

The STRATAA study protocol: a programme to assess the burden of enteric fever in Bangladesh, Malawi and Nepal using prospective population census, passive surveillance, serological studies and healthcare utilisation surveys.

Introduction Invasive infections caused by Salmonella enterica serovar Typhi and Paratyphi A are estimated to account for 12–27 million febrile illness episodes worldwide annually. Determining the true burden of typhoidal Salmonellae infections is hindered by lack of population-based studies and adequate laboratory diagnostics. The Strategic Typhoid alliance across Africa and Asia study takes a systematic approach to measuring the age-stratified burden of clinical and subclinical disease caused by typhoidal Salmonellae infections at three high-incidence urban sites in Africa and Asia. We aim to explore the natural history of Salmonella transmission in endemic settings, addressing key uncertainties relating to the epidemiology of enteric fever identified through mathematical models, and enabling optimisation of vaccine strategies. Methods/design Using census-defined denominator populations of ≥100 000 individuals at sites in Malawi, Bangladesh and Nepal, the primary outcome is to characterise the burden of enteric fever in these populations over a 24-month period. During passive surveillance, clinical and household data, and laboratory samples will be collected from febrile individuals. In parallel, healthcare utilisation and water, sanitation and hygiene surveys will be performed to characterise healthcare-seeking behaviour and assess potential routes of transmission. The rates of both undiagnosed and subclinical exposure to typhoidal Salmonellae (seroincidence), identification of chronic carriage and population seroprevalence of typhoid infection will be assessed through age-stratified serosurveys performed at each site. Secondary attack rates will be estimated among household contacts of acute enteric fever cases and possible chronic carriers. Ethics and dissemination This protocol has been ethically approved by the Oxford Tropical Research Ethics Committee, the icddr,b Institutional Review Board, the Malawian National Health Sciences Research Committee and College of Medicine Research Ethics Committee and Nepal Health Research Council. The study is being conducted in accordance with the principles of the Declaration of Helsinki and Good Clinical Practice. Informed consent was obtained before study enrolment. Results will be submitted to international peer-reviewed journals and presented at international conferences. Trial registration number ISRCTN 12131979. Ethics references Oxford (Oxford Tropical Research Ethics Committee 39-15). Bangladesh (icddr,b Institutional Review Board PR-15119). Malawi (National Health Sciences Research Committee 15/5/1599). Nepal (Nepal Health Research Council 306/2015)

The Typhoid Vaccine Acceleration Consortium (TyVAC): Vaccine effectiveness study designs: Accelerating the introduction of typhoid conjugate vaccines and reducing the global burden of enteric fever. Report from a meeting held on 26-27 October 2016, Oxford, UK

Typhoid fever is estimated to cause between 11.9–26.9 million infections globally each year with 129,000–216,510 deaths. Access to improved water sources have reduced disease incidence in parts of the world but the use of efficacious vaccines is seen as an important public health tool for countries with a high disease burden. A new generation of Vi typhoid conjugate vaccines (TCVs), licensed for use in young children and expected to provide longer lasting protection than previous vaccines, are now available. The WHO Strategic Advisory Group of Experts on Immunization (SAGE) has convened a working group to review the evidence on TCVs and produce an updated WHO position paper for all typhoid vaccines in 2018 that will inform Gavi, the Vaccine Alliance's future vaccine investment strategies for TCVs. The Typhoid Vaccine Acceleration Consortium (TyVAC) has been formed through a $36.9 million funding program from the Bill & Melinda Gates Foundation to accelerate the introduction of TCVs into Gavi-eligible countries. In October 2016, a meeting was held to initiate planning of TCV effectiveness studies that will provide the data required by policy makers and stakeholders to support decisions on TCV use in countries with a high typhoid burden. Discussion topics included (1) the latest evidence and data gaps in typhoid epidemiology; (2) WHO and Gavi methods and data requirements; (3) data on TCV efficacy; (4) cost effectiveness analysis for TCVs from mathematical models; (5) TCV delivery and effectiveness study design. Specifically, participants were asked to comment on study design in 3 sites for which population-based typhoid surveillance is underway. The conclusion of the meeting was that country-level decision making would best be informed by the respective selected sites in Africa and Asia vaccinating children aged from 9-months to 15-years-old, employing either an individual or cluster randomized design with design influenced by population characteristics, transmission dynamics, and statistical considerations

A Bayesian approach for estimating typhoid fever incidence from large‐scale facility‐based passive surveillance data

Decisions about typhoid fever prevention and control are based on estimates of typhoid incidence and their uncertainty. Lack of specific clinical diagnostic criteria, poorly sensitive diagnostic tests, and scarcity of accurate and complete datasets contribute to difficulties in calculating age-specific population-level typhoid incidence. Using data from the Strategic Typhoid Alliance across Africa and Asia program, we integrated demographic censuses, healthcare utilization surveys, facility-based surveillance, and serological surveillance from Malawi, Nepal, and Bangladesh to account for under-detection of cases. We developed a Bayesian approach that adjusts the count of reported blood-culture-positive cases for blood culture detection, blood culture collection, and healthcare seeking—and how these factors vary by age—while combining information from prior published studies. We validated the model using simulated data. The ratio of observed to adjusted incidence rates was 7.7 (95% credible interval [CrI]: 6.0-12.4) in Malawi, 14.4 (95% CrI: 9.3-24.9) in Nepal, and 7.0 (95% CrI: 5.6-9.2) in Bangladesh. The probability of blood culture collection led to the largest adjustment in Malawi, while the probability of seeking healthcare contributed the most in Nepal and Bangladesh; adjustment factors varied by age. Adjusted incidence rates were within or below the seroincidence rate limits of typhoid infection. Estimates of blood-culture-confirmed typhoid fever without these adjustments results in considerable underestimation of the true incidence of typhoid fever. Our approach allows each phase of the reporting process to be synthesized to estimate the adjusted incidence of typhoid fever while correctly characterizing uncertainty, which can inform decision-making for typhoid prevention and control

Burden of enteric fever at three urban sites in Africa and Asia: a multicentre population-based study

Background Enteric fever is a serious public health concern in many low-income and middle-income countries. Numerous data gaps exist concerning the epidemiology of Salmonella enterica serotype Typhi (S Typhi) and Salmonella enterica serotype Paratyphi (S Paratyphi), which are the causative agents of enteric fever. We aimed to determine the burden of enteric fever in three urban sites in Africa and Asia. Methods In this multicentre population-based study, we did a demographic census at three urban sites in Africa (Blantyre, Malawi) and Asia (Kathmandu, Nepal and Dhaka, Bangladesh) between June 1, 2016, and Sept 25, 2018. Households were selected randomly from the demographic census. Participants from within the geographical census area presenting to study health-care facilities were approached for recruitment if they had a history of fever for 72 h or more (later changed to >48 h) or temperature of 38·0°C or higher. Facility-based passive surveillance was done between Nov 11, 2016, and Dec 31, 2018, with blood-culture collection for febrile illness. We also did a community-based serological survey to obtain data on Vi-antibody defined infections. We calculated crude incidence for blood-culture-confirmed S Typhi and S Paratyphi infection, and calculated adjusted incidence and seroincidence of S Typhi blood-culture-confirmed infection. Findings 423 618 individuals were included in the demographic census, contributing 626 219 person-years of observation for febrile illness surveillance. 624 S Typhi and 108 S Paratyphi A isolates were collected from the blood of 12 082 febrile patients. Multidrug resistance was observed in 44% S Typhi isolates and fluoroquinolone resistance in 61% of S Typhi isolates. In Blantyre, the overall crude incidence of blood-culture confirmed S Typhi was 58 cases per 100 000 person-years of observation (95% CI 48–70); the adjusted incidence was 444 cases per 100 000 person-years of observation (95% credible interval [CrI] 347–717). The corresponding rates were 74 (95% CI 62–87) and 1062 (95% CrI 683–1839) in Kathmandu, and 161 (95% CI 145–179) and 1135 (95% CrI 898–1480) in Dhaka. S Paratyphi was not found in Blantyre; overall crude incidence of blood-culture-confirmed S Paratyphi A infection was 6 cases per 100 000 person-years of observation (95% CI 3–11) in Kathmandu and 42 (95% CI 34–52) in Dhaka. Seroconversion rates for S Typhi infection per 100 000 person-years estimated from anti-Vi seroconversion episodes in serological surveillance were 2505 episodes (95% CI 1605–3727) in Blantyre, 7631 (95% CI 5913–9691) in Kathmandu, and 3256 (95% CI 2432–4270) in Dhaka. Interpretation High disease incidence and rates of antimicrobial resistance were observed across three different transmission settings and thus necessitate multiple intervention strategies to achieve global control of these pathogens. Funding Wellcome Trust and the Bill & Melinda Gates Foundation

Direct inference and control of genetic population structure from RNA sequencing data

RNAseq data can be used to infer genetic variants, yet its use for estimating genetic population structure remains underexplored. Here, we construct a freely available computational tool (RGStraP) to estimate RNAseq-based genetic principal components (RG-PCs) and assess whether RG-PCs can be used to control for population structure in gene expression analyses. Using whole blood samples from understudied Nepalese populations and the Geuvadis study, we show that RG-PCs had comparable results to paired array-based genotypes, with high genotype concordance and high correlations of genetic principal components, capturing subpopulations within the dataset. In differential gene expression analysis, we found that inclusion of RG-PCs as covariates reduced test statistic inflation. Our paper demonstrates that genetic population structure can be directly inferred and controlled for using RNAseq data, thus facilitating improved retrospective and future analyses of transcriptomic data

Modeling the potential impact of typhoid conjugate vaccines

Mathematical modeling of the transmission dynamics of Salmonella Typhi allows for an evaluation of the potential impact of vaccination and a quantification of the expected direct and indirect effects of vaccines under a variety of scenarios regarding vaccine efficacy and program implementation. We developed an age-structured compartmental model that reflects the natural history and immune response to infection with Salmonella Typhi. We fit our model to data on culture-confirmed cases of typhoid fever from a variety of settings in South Asia in order to estimate important model parameters, such as the basic reproductive number (R0). We then evaluated the potential impact of routine vaccination and/or vaccination campaigns targeted at different age groups. We parameterized the vaccine efficacy and duration of protection based on data for Vi-polysaccharide and Vi-conjugate vaccines. Our model was able to reproduce the incidence pattern and age distribution of typhoid cases in Vellore, India; Kathmandu, Nepal; and Dhaka, Bangladesh for different values of R0 in these settings. Vaccination was predicted to confer substantial indirect protection in the short term, leading to a decrease in the incidence of typhoid. However, waning of vaccine-induced immunity could lead to a rebound in typhoid incidence 5-15 years after vaccine introduction. Model predictions for the overall and indirect effects of typhoid vaccination and prospects for elimination depend strongly on the role of chronic carriers in transmission. Elucidating the role of chronic carriers in transmission in different settings is a pivotal area for future epidemiological research. Our results suggest that is unlikely that typhoid can be eliminated from high incidence endemic settings through vaccination alone

Epidemic Dynamics at the Human-Animal Interface

Few infectious diseases are entirely human-specific: most human pathogens also circulate in animals, or else originated in non-human hosts. Influenza, plague, and trypanosomiasis are classic examples of zoonoses, or infections that transmit from animals to humans. The multi-host ecology of zoonoses leads to complex dynamics, and analytical tools such as mathematical modeling are vital to the development of effective control policies and research agendas. Much attention has focused on modeling pathogens with simpler life cycles and immediate global urgency, such as influenza and SARS, but vector-transmitted, chronic, and protozoan infections have been neglected, as have crucial processes such as cross-species transmission. Progress in understanding and combating zoonoses requires a new generation of models that addresses a broader set of pathogen life histories and integrates across host species and scientific disciplines

Demographic Variability, Vaccination, and the Spatiotemporal Dynamics of Rotavirus Epidemics

Historically, annual rotavirus activity in the United States has started in the southwest in late fall and ended in the northeast 3 months later; this trend has diminished in recent years. Traveling waves of infection or local environmental drivers cannot account for these patterns. A transmission model calibrated against epidemiological data shows that spatiotemporal variation in birth rate can explain the timing of rotavirus epidemics. The recent large-scale introduction of rotavirus vaccination provides a natural experiment to further test the impact of susceptible recruitment on disease dynamics. The model predicts a pattern of reduced and lagged epidemics postvaccination, closely matching the observed dynamics. Armed with this validated model, we explore the relative importance of direct and indirect protection, a key issue in determining the worldwide benefits of vaccination