Project description:BACKGROUND AND AIMS:Hepatitis C virus (HCV) and its sequelae present a significant source of economic and societal burden. Introduction of highly effective curative therapies has made HCV elimination attainable. The study used a predictive model to assess the clinical and economic impact of implementing national screening and treatment policies toward HCV elimination in Korea. METHODS:A previously validated Markov disease progression model of HCV infection was employed to analyze the clinical and economic impact of various strategies for HCV diagnosis and treatment in Korea. In this analysis, the model compared the clinical and economic outcomes of current HCV-related interventions in Korea (7,000 patients treated and 4,200 patients newly diagnosed annually, starting in 2017) to four elimination scenarios: 1) initiating sufficient diagnosis and treatment interventions to meet the World Health Organization's GHSS elimination targets by 2030, 2) delaying initiation of interventions by one year, 3) delaying initiation of interventions by two years and 4) accelerating initiation of interventions to meet elimination targets by 2025. Modelled historical incidence of HCV was calibrated to match a viremic HCV prevalence of 0.44% in 2009. Elimination scenarios required 24,000 treatments and 34,000 newly diagnosed patients annually, starting in 2018, to reach the 2030 targets. RESULTS:Compared to current "status quo" interventions, elimination (or accelerated elimination by 2025) would avert 23,700 (27,000) incident cases of HCV, 1,300 (1,400) liver-related deaths (LRDs) and 2,900 (3,100) cases of end-stage liver disease (ESLD) over the 2017-2030 time period. Postponing interventions by one (or two) years would avert 21,100 (18,600) new HCV infections, 920 (660) LRDs and 2,000 (1,400) cases of ESLD by 2030. Following elimination or accelerated elimination strategies would save 860 million USD or 1.1 billion USD by 2030, respectively, compared to the status quo, requiring an up-front investment in prevention that decreases spending on liver-related complications and death. CONCLUSIONS:By projecting the impact of interventions and tracking progress toward GHSS elimination targets using modelling, we demonstrate that Korea can prevent significant morbidity, mortality and spending on HCV. Results should serve as the backbone for policy and decision-making, demonstrating how aggressive prevention measures are designed to reduce future costs and increase the health of the public.

Project description:BackgroundMalaria was once one of the most serious public health problems in China. However, the disease burden has sharply declined and epidemic areas have shrunk after the implementation of an integrated malaria control and elimination strategy, especially since 2000. In this review, the lessons were distilled from the Chinese national malaria elimination programme and further efforts to mitigate the challenges of malaria resurgence are being discussed.MethodsA retrospective evaluation was performed to assess the changes in malaria epidemic patterns from 1950 to 2017 at national level. The malaria data before 2004 were collected from paper-based annual reports. After 2004, each of the different cases from the Infectious Diseases Information Reporting Management System (IDIRMS) was closely examined and scrutinized. An additional documenting system, the National Information Management System for Malaria, established in 2012 to document the interventions of three parasitic diseases, was also examined to complete the missing data from IDIRMS.ResultsFrom 1950 to 2017, the occurrence of indigenous malaria has been steeply reduced, and malaria-epidemic regions have substantially shrunk, especially after the launch of the national malaria elimination programme. There were approximately 30 million malaria cases annually before 1949 with a mortality rate of 1%. A total of 5999 indigenous cases were documented from 2010 to 2016, with a drastic reduction of 99% over the 6 years (2010, n?=?4262; 2016, n?=?3). There were indigenous cases reported in 303 counties from 18 provinces in 2010, but only 3 indigenous cases were reported in 2 provinces nationwide in 2016. While in 2017, for the first time, zero indigenous case was reported in China, and only 7 of imported cases were in individuals who died of Plasmodium falciparum infection.ConclusionMalaria elimination in China is a country-led and country-owned endeavour. The country-own efforts were a clear national elimination strategy, supported by two systems, namely a case-based surveillance and response system and reference laboratory system. The country-led efforts were regional and inter-sectoral collaboration as well as sustained monitoring and evaluation. However, there are still some challenges, such as the maintenance of non-transmission status, the implementation of a qualified verification and assessment system, and the management of imported cases in border areas, through regional cooperation. The findings from this review can probably help improving malaria surveillance systems in China, but also in other elimination countries.

Project description:The 'Ending the HIV Epidemic (EHE)' national plan aims to reduce annual HIV incidence in the United States from 38,000 in 2015 to 9300 by 2025 and 3300 by 2030. Diagnosis and treatment are two most effective interventions, and thus, identifying corresponding optimal combinations of testing and retention-in-care rates would help inform implementation of relevant programs. Considering the dynamic and stochastic complexity of the disease and the time dynamics of decision-making, solving for optimal combinations using commonly used methods of parametric optimization or exhaustive evaluation of pre-selected options are infeasible. Reinforcement learning (RL), an artificial intelligence method, is ideal; however, training RL algorithms and ensuring convergence to optimality are computationally challenging for large-scale stochastic problems. We evaluate its feasibility in the context of the EHE goal. We trained an RL algorithm to identify a 'sequence' of combinations of HIV-testing and retention-in-care rates at 5-year intervals over 2015-2070 that optimally leads towards HIV elimination. We defined optimality as a sequence that maximizes quality-adjusted-life-years lived and minimizes HIV-testing and care-and-treatment costs. We show that solving for testing and retention-in-care rates through appropriate reformulation using proxy decision-metrics overcomes the computational challenges of RL. We used a stochastic agent-based simulation to train the RL algorithm. As there is variability in support-programs needed to address barriers to care-access, we evaluated the sensitivity of optimal decisions to three cost-functions. The model suggests to scale-up retention-in-care programs to achieve and maintain high annual retention-rates while initiating with a high testing-frequency but relaxing it over a 10-year period as incidence decreases. Results were mainly robust to the uncertainty in costs. However, testing and retention-in-care alone did not achieve the 2030 EHE targets, suggesting the need for additional interventions. The results from the model demonstrated convergence. RL is suitable for evaluating phased public health decisions for infectious disease control.

Project description:Genomic surveillance is an important aspect of contemporary disease management but has yet to be used routinely to monitor endemic disease transmission and control in low- and middle-income countries. Rabies is an almost invariably fatal viral disease that causes a large public health and economic burden in Asia and Africa, despite being entirely vaccine preventable. With policy efforts now directed towards achieving a global goal of zero dog-mediated human rabies deaths by 2030, establishing effective surveillance tools is critical. Genomic data can provide important and unique insights into rabies spread and persistence that can direct control efforts. However, capacity for genomic research in low- and middle-income countries is held back by limited laboratory infrastructure, cost, supply chains and other logistical challenges. Here we present and validate an end-to-end workflow to facilitate affordable whole genome sequencing for rabies surveillance utilising nanopore technology. We used this workflow in Kenya, Tanzania and the Philippines to generate rabies virus genomes in two to three days, reducing costs to approximately £60 per genome. This is over half the cost of metagenomic sequencing previously conducted for Tanzanian samples, which involved exporting samples to the UK and a three- to six-month lag time. Ongoing optimization of workflows are likely to reduce these costs further. We also present tools to support routine whole genome sequencing and interpretation for genomic surveillance. Moreover, combined with training workshops to empower scientists in-country, we show that local sequencing capacity can be readily established and sustainable, negating the common misperception that cutting-edge genomic research can only be conducted in high resource laboratories. More generally, we argue that the capacity to harness genomic data is a game-changer for endemic disease surveillance and should precipitate a new wave of researchers from low- and middle-income countries.

Dataset Information

A Tool to Inform Hepatitis C Elimination: A Case for Hepatitis C Elimination in China.

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