FutureDreams

While economists talk about Africa’s demographic dividend,Bill Gates,Co-chair of the Bill&Melinda Gates Foundation,regards the continent’s young population as vital for its growth because of their power to innovate without being bogged down by

Equal Partnership in Agriculture

It was wonderful to be back in China in June for the Third China-Africa Economic and Trade Expo(CAETE)in the city of Changsha,Hunan Province.Since its inauguration in 2019,the CAETE has become an important platform for expanding the China-Africa relationship,of which agricultural cooperation is an increasingly significant element.The scale of the activities in Changsha was testament to the scope and ambition of all those involved in China-Africa exchanges.

Access to and affordability of healthcare for TB patients in China: issues and challenges

This paper introduces the background,aim and objectives of the project entitled“China—the Gates Foundation Collaboration on TB Control in China”that has been underway for many years.It also summarizes the key findings of the nine papers included in this special issue,which used data from the baseline survey of Phase II of the project.Data were collected from the survey of TB and MDR-TB patients,from designated hospitals,health insurance agencies and the routine health information systems,as well as key informant interviews and focus group discussions with relevant key stakeholders.Key issues discussed in this series of papers include the uses of TB services and anti-TB medicines and their determining factors related to socio-economic and health systems development;expenditures on TB care and the financial burden incurred on TB patients;and the impact of health insurance schemes implemented in China on financial protection.

Factors that associated with TB patient admission rate and TB inpatient service cost: a cross-sectional study in China

Background:China has recently adopted the“TB designated hospital model”to improve the quality of tuberculosis(TB)treatment and patient management.Considering that inpatient service often results in high patient financial burden,and therefore influences patient adherence to treatment,it is critical to better understand the TB patient admission rate and TB inpatient service cost,as well as their influential factors in this new model.Methods:Quantitative and qualitative studies were conducted in two cities,Hanzhong in Shaanxi Province and Zhenjiang in Jiangsu Province,in China.Quantitative data were obtained from a sample survey of 533 TB patients and TB inpatient records from 2010–2012 in six county designated hospitals.Qualitative information was obtained through interviews with key stakeholders(40 key informant interviews,14 focus group discussions)and reviews of health policy documents in study areas.Both univariate and multivariate statistical analyses were applied for the quantitative analysis,and the thematic framework approach was applied for the qualitative analysis.Results:The TB patient admission rates in Zhenjiang and Hanzhong were 54.8 and 55.9%,respectively.Qualitative analyses revealed that financial incentives,misunderstanding of infectious disease control and failure of health insurance regulations were the key factors associated with the admission rates and medical costs.Quantitative analyses found differences in hospitalization rate existed among patients with different health insurance and patients from different counties.Average medical costs for TB inpatients in Jurong and Zhenba were 7,215 CNY and 4,644 CNY,which was higher than the 5,500 CNY and 3,800 CNY limits set by the New Rural Cooperative Medical System.No differences in medical cost or length of stay were found between patients with and without comorbidities in county-level hospitals.Conclusions:TB patient admission rates and inpatient service costs were relatively high.Studies of related factors indicated that a package of interventions,including health education programs,reform of health insurance regulations and improvement of TB treatment guidelines,are urgently required to ensure that TB patients receive appropriate care.

Impact of an innovative financing and payment model on tuberculosis patients'financial burden:is tuberculosis care more affordable for the poor?

Background:In response to the high financial burden of health services facing tuberculosis(TB)patients in China,the China-Gates TB project,PhaseⅡ,has implemented a new financing and payment model as an important component of the overall project in three cities in eastern,central and western China.The model focuses on increasing the reimbursement rate for TB patients and reforming provider payment methods by replacing fee-for-service with a case-based payment approach.This study investigated changes in out-of-pocket(OOP)health expenditure and the financial burden on TB patients before and after the interventions,with a focus on potential differential impacts on patients from different income groups.Methods:Three sample counties in each of the three prefectures:Zhenjiang,Yichang and Hanzhong were chosen as study sites.TB patients who started and completed treatment before,and during the intervention period,were randomly sampled and surveyed at the baseline in 2013 and final evaluation in 2015 respectively.OOP health expenditure and percentage of patients incurring catastrophic health expenditure(CHE)were calculated for different income groups.OLS regression and Iogit regression were conducted to explore the intervention's impacts on patient OOP health expenditure and financial burden after adjusting for other covariates.Key-informant interviews and focus group discussions were conducted to understand the reasons for any observed changes.Results:Data from 738(baseline)and 735(evaluation)patients were available for analysis.Patient mean OOP health expenditure increased from RMB 3576 to RMB 5791,and the percentage of patients incurring CHE also increased after intervention.The percentage increase in OOP health expenditure and the likelihood of incurring CHE were significantly lower for patients from the highest income group as compared to the lowest.Qualitative findings indicated that increased use of health services not covered by the standard package of the model was likely to have caused the increase in financial burden.Conclusions:The implementation of the new financing and payment model did not protect patients,especially those from the lowest income group,from financial difficulty,due partly to their increased use of health service.More financial resources should be mobilized to increase financial protection,particularly for poor patients,while cost containment strategies need to be developed and effectively implemented to improve the effective coverage of essential healthcare in China.

The Impact of COVID-19 on Tuberculosis Patients’Behavior of Seeking Medical Care——China,2020

Summary What is already known on this topic?The coronavirus disease 2019(COVID-19)pandemic has disrupted the tuberculosis(TB)service system.However,the impact on TB patients in China remains unknown.What is added by this report?This report firstly addressed the impact of COVID-19 on TB patients in China.About half of TB patients did not revisit the hospital due to personal reasons.The reasons for irregular medication and postponing or cancelling examination after full treatment course were different.

Multichannel Financing Reduces Economic Burden and Improves the Medical Security Level for Tuberculosis Patients

Tuberculosis(TB)is one of the main infectious diseases to simultaneously cause poverty and be caused by poverty.Reducing the economic burden of TB patients in China is essential to improving patient compliance and reducing the impact of the TB epidemic.In accordance with the national reform of the medical and health system and the current status of the country’s TB prevention and treatment service system,representatives of the government proposed the concept of a multichannel financing mechanism.

Use of anti-tuberculosis drugs among newly diagnosed pulmonary tuberculosis inpatients in China: a retrospective study

Background:China’s national tuberculosis control program(NTP)provides free,first-line anti-tuberculosis(TB)drugs to pulmonary TB patients.This treatment regimen follows the World Health Organization’s(WHO)guideline.The objective of this paper is to evaluate the current status of anti-TB drug use for newly diagnosed pulmonary TB inpatients treated in prefecture-and county-level designated hospitals.Methods:Three prefecture-level hospitals and nine county-level hospitals were selected for the study.All newly diagnosed pulmonary TB inpatient medical records from 2012 were reviewed and doubly examined by two national senior physicians.The rational use of anti-TB drugs was evaluated based on criteria in line with WHO’s guideline.Results:Of the 2,060 total treatment regimens for TB,53.1%were found to be rational(1093/2060).The percentages in prefecture-level and county-level hospitals were 50.3%(761/1513)and 60.7%(332/547),respectively.The difference between the two levels of hospitals was statistically significant(Chi-square value=17.44,P<0.01).The percentages of rational treatment regimens for first-time hospitalizations and for two or more hospitalizations were 59.5%(983/1653)and 27.0%(110/407),respectively,with a statistically significant difference(Chi-square value=138.00,P<0.01).The overall use of second-line drugs(SLD)was 54.9%(1131/2060).The percentages for prefecture-level and county-level hospitals were 50.6%(766/1513)and 66.7%(365/547),respectively.A statistically significant difference was found(Chi-square value=42.06,P<0.01).The use of SLD for inpatients hospitalized once and inpatients hospitalized twice or more was 58.4%(966/1653)and 40.5%(165/407),respectively,with a statistically significant difference(Chi-square value=42.26,P<0.01).Conclusions:Half of inpatients might be treated with irrational regimens,and the use of SLD was more appropriately dispensed in city-level hospitals than in county-level hospitals.Trainings and guidelines for health personnel,supervision led by health authorities and increased investment to designated hospitals may help to improve the rational use of anti-TB drugs.

Effectiveness of the Integrated TB Surveillance System--China,2018-2019

What is already known about this topic?China’s national health information system provides important support and means for deepening the country’s medical and health reform,for improving relevant delivery services,for enhancing the level of scientific management of health,and for promoting the goal of basic medical and health services for everyone in China.What is added by this report?To further the construction of the national health information system,the National Center for Tuberculosis Control and Prevention of China CDC,started a pilot project for a new tuberculosis(TB)integrated health(iHealth)surveillance system,which was integrated with regional health information platforms.The goal was to explore automatic data exchange between hospitals and disease control facilities to reduce the workload of data-entry.What are the implications for public health practice?This pilot proved that data sharing and automatic exchanges between different information systems can be achieved through a unified surveillance dataset,which could provide a reference point for the construction of surveillance systems for other infectious diseases or for the entire public health information system.

Agent-based modeling of COVID-19 outbreaks for New York state and UK:Parameter identification algorithm

This paper uses Covasim,an agent-based model(ABM)of COVID-19,to evaluate and scenarios of epidemic spread in New York State(USA)and the UK.Epidemiological parameters such as contagiousness(virus transmission rate),initial number of infected people,and probability of being tested depend on the region's demographic and geographical features,the containment measures introduced;they are calibrated to data about COVID-19 spread in the region of interest.At the first stage of our study,epidemiological data(numbers of people tested,diagnoses,critical cases,hospitalizations,and deaths)for each of the mentioned regions were analyzed.The data were characterized in terms of seasonality,stationarity,and dependency spaces,and were extrapolated using machine learning techniques to specify unknown epidemiological parameters of the model.At the second stage,the Optuna optimizer based on the tree Parzen estimation method for objective function minimization was applied to determine the model's unknown parameters.The model was validated with the historical data of 2020.The modeled results of COVID-19 spread in New York State and the UK have demonstrated that if the level of testing and containment measures is preserved,the number of positive cases in New York State remain the same during March of 2021,while in the UK it will reduce.

Leveraging mathematical models of disease dynamics and machine learning to improve development of novel malaria interventions

Background:Substantial research is underway to develop next-generation interventions that address current malaria control challenges.As there is limited testing in their early development,it is difficult to predefine intervention properties such as efficacy that achieve target health goals,and therefore challenging to prioritize selection of novel candidate interventions.Here,we present a quantitative approach to guide intervention development using mathematical models of malaria dynamics coupled with machine learning.Our analysis identifies requirements of efficacy,coverage,and duration of effect for five novel malaria interventions to achieve targeted reductions in malaria prevalence.Methods:A mathematical model of malaria transmission dynamics is used to simulate deployment and predict potential impact of new malaria interventions by considering operational,health-system,population,and disease characteristics.Our method relies on consultation with product development stakeholders to define the putative space of novel intervention specifications.We couple the disease model with machine learning to search this multi-dimensional space and efficiently identify optimal intervention properties that achieve specified health goals.Results:We apply our approach to five malaria interventions under development.Aiming for malaria prevalence reduction,we identify and quantify key determinants of intervention impact along with their minimal properties required to achieve the desired health goals.While coverage is generally identified as the largest driver of impact,higher efficacy,longer protection duration or multiple deployments per year are needed to increase prevalence reduction.We show that interventions on multiple parasite or vector targets,as well as combinations the new interventions with drug treatment,lead to significant burden reductions and lower efficacy or duration requirements.Conclusions:Our approach uses disease dynamic models and machine learning to support decision-making and resource investment,facilitating development of new malaria interventions.By evaluating the intervention capabilities in relation to the targeted health goal,our analysis allows prioritization of interventions and of their specifications from an early stage in development,and subsequent investments to be channeled cost-effectively towards impact maximization.This study highlights the role of mathematical models to support intervention development.Although we focus on five malaria interventions,the analysis is generalizable to other new malaria interventions.