Centralization vs. Decentralization in COVID-19 Responses: Lessons from China

Researchers have begun to examine whether centralized or decentralized (or federal) political systems have better handled the COVID-19 pandemic. In this paper, we probe beneath the surface of China’s political system to examine the balance between centralized and decentralized authority in China’s handling of the pandemic. We show that after the SARS epidemic of 2003, China adjusted the central–local balance of authority over systems to handle both the detection and early response phases of health emergencies. In an attempt to overcome problems revealed by SARS, it sought both to centralize early infectious disease reporting and to decentralize authority to respond to local health emergencies. But these adjustments in the central–local balance of authority after SARS did not change “normal times” authority relations and incentive structures in the political system. As a result, local leaders had both the authority and the incentive to prioritize tasks that determine their political advancement at the cost of containing the spread of COVID-19. China’s efforts to balance central and local authority shows just how difficult it is to get it right, especially in the early phase of a pandemic.

Environmental factors and spatiotemporal distribution of Japanese encephalitis after vaccination campaign in Guizhou Province, China (2004–2016)

Background Although a vaccination campaign has been conducted since 2004, Japanese encephalitis (JE) is still a public health problem in Guizhou, one of the provinces with the highest incidence of JE in China. The aim of this study was to understand the spatiotemporal distribution of JE and its relationship with environmental factors in Guizhou Province in the post-vaccination era, 2004–2016. Methods We collected data on human JE cases in Guizhou Province from 2004 to 2016 from the national infectious disease reporting system. A Poisson regression model was used to analyze the relationship between JE occurrence and environmental factors amongst counties. Results Our results showed that the incidence and mortality of JE decreased after the initiation of vaccination. JE cases were mainly concentrated in preschool and school-age children and the number of cases in children over age 15 years was significantly decreased compared with the previous 10 years; the seasonality of JE before and after the use of vaccines was unchanged. JE incidence was positively associated with cultivated land and negatively associated with gross domestic product (GDP) per capita, vegetation coverage, and developed land. In areas with cultivated land coverage < 25%, vegetation coverage > 55%, and urban area coverage > 25%, the JE risk was lower. The highest JE incidence was among mid-level GDP areas and in moderately urbanized areas. Conclusions This study assessed the relationship between incidence of JE and environmental factors in Guizhou Province. Our results highlight that the highest risk of JE transmission in the post-vaccination era is in mid-level developed areas.

Changes to Timeliness and Completeness of Infectious Disease Reporting in Texas After Implementation of an Epidemiologic Capacity Program

Objectives The objective of this study was to characterize the changes in timeliness and completeness of disease case reporting in Texas in response to an increasing number of foodborne illnesses and high-consequence infectious disease investigations and the Texas Department of State Health Services’ new state-funded epidemiologist (SFE) program. Methods We extracted electronic disease case reporting data on 42 conditions from 2012 through 2016 in all local health department (LHD) jurisdictions. We analyzed data on median time for processing reports and percentage of complete reports across time and between SFE and non-SFE jurisdictions using Mann–Whitney t tests and z scores. Results The median time of processing improved from 13 days to 10 days from 2012 to 2016, and the percentage of disease case reports that were complete improved from 19.6% to 27.7%. Most reports were for foodborne illnesses; both timeliness (11 to 7 days) and completeness (20.9% to 23.5%) improved for these reports. Conclusions Disease reporting improvements in timeliness and completeness were associated with the SFE program and its enhancement of epidemiologic capacity. SFEs were shown to improve surveillance metrics in LHDs, even in jurisdictions with a high volume of case reports. Adding epidemiologist positions in LHDs produces a tangible outcome of improved disease surveillance.

Assessing the Quality of Reporting to China’s National TB Surveillance Systems

(1) Background: The reliability of disease surveillance may be restricted by sensitivity or ability to capture all disease. Objective: To quantify under-reporting and concordance of recording persons with tuberculosis (TB) in national TB surveillance systems: the Infectious Disease Reporting System (IDRS) and Tuberculosis Information Management System (TBIMS). (2) Methods: This retrospective review includes 4698 patients identified in 2016 in China. County staff linked TB patients identified from facility-specific health and laboratory information systems with records in IDRS and TBIMS. Under-reporting was calculated, and timeliness, concordance, accuracy, and completeness were analyzed. Multivariable logistic regression was used to examine factors associated with under-reporting. (3) Results: We found that 505 (10.7%) patients were missing within IDRS and 1451 (30.9%) patients were missing within TBIMS. Of 171 patient records reviewed in IDRS and 170 patient records in TBIMS, 12.3% and 6.5% were found to be untimely, and 10.7% and 7.1% were found to have an inconsistent home address. The risk of under-reporting to both IDRS and TBIMS was greatest at tertiary health facilities and among non-residents; the risk of under-reporting to TBIMS was greatest with patients aged 65 or older and with extrapulmonary TB (EPTB). (4) Conclusions: It is important to improve the reporting and recording of TB patients. Local TB programs that focus on training, and mentoring high-burden hospitals, facilities that cater to EPTB, and migrant patients may improve reporting and recording.

Geocoding cryptosporidiosis cases in Ireland (2008–2017)—development of a reliable, reproducible, multiphase geocoding methodology

Background Geocoding (the process of converting a text address into spatial data) quality may affect geospatial epidemiological study findings. No national standards for best geocoding practice exist in Ireland. Irish postcodes (Eircodes) are not routinely recorded for infectious disease notifications and > 35% of dwellings have non-unique addresses. This may result in incomplete geocoding and introduce systematic errors into studies. Aims This study aimed to develop a reliable and reproducible methodology to geocode cryptosporidiosis notifications to fine-resolution spatial units (Census 2016 Small Areas), to enhance data validity and completeness, thus improving geospatial epidemiological studies. Methods A protocol was devised to utilise geocoding tools developed by the Health Service Executive’s Health Intelligence Unit. Geocoding employed finite-string automated and manual matching, undertaken sequentially in three additive phases. The protocol was applied to a cryptosporidiosis notification dataset (2008–2017) from Ireland’s Computerised Infectious Disease Reporting System. Outputs were validated against devised criteria. Results Overall, 92.1% (4266/4633) of cases were successfully geocoded to one Small Area, and 95.5% (n = 4425) to larger spatial units. The proportion of records geocoded increased by 14% using the multiphase approach, with 5% of records re-assigned to a different spatial unit. Conclusions The developed multiphase protocol improved the completeness and validity of geocoding, thus increasing the power of subsequent studies. The authors recommend capturing Eircodes ideally using application programming interface for infectious disease or other health-related datasets, for more efficient and reliable geocoding. Where Eircodes are not recorded/available, for best geocoding practice, we recommend this (or a similar) quality driven protocol.

Epidemiological and time series analysis on the incidence and death of AIDS and HIV in China

Background To investigate the regional and age-specific distribution of AIDS/HIV in China from 2004 to 2017 and to conduct time series analysis of the epidemiological trends. Method Using official surveillance data from publicly accessible database of the national infectious disease reporting system, we described long-term patterns of incidence and death in AIDS/HIV, analyzed age group and regional epidemic characteristics, and established Autoregressive Integrated Moving Average (ARIMA) models for time series analysis. Result The incidence and death of AIDS/HIV have increased rapidly from 2004 to 2017, with significant difference regarding age groups and provincial regions (a few provinces appear as hot spots). With goodness-of-fit criteria and using data from 2004 to 2015, ARIMA (0,1,3) × (2,0,0), ARIMA (3,1,0) × (1,0,1), and ARIMA (0,1,2) × (2,0,0) were chosen as the optimal model for the incidence of AIDS, HIV, and combined; ARIMA (0,1,3) × (1,0,0) was chosen as the optimal model for the death of AIDS, HIV, and combined. ARIMA models robustly predicted the incidence and death of AIDS/HIV in 2016 and 2017. Conclusion A focused intervention strategy targeting specific regions and age groups is essential for the prevention and control of AIDS/HIV. ARIMA models function as data-driven and evidence-based methods to forecast the trends of infectious diseases and formulate public health policies.

Assessing the Quality of Reporting to China's National TB Surveillance Systems

Background: The reliability of disease surveillance may be restricted by sensitivity or the ability of the system to capture all disease. Our objective was to quantify under-reporting and concordance of recording persons with tuberculosis (TB) in the national TB surveillance systems: Infectious Disease Reporting System (IDRS) and TB Information Management System (TBIMS). Methods: This retrospective review includes patients identified in 2016 from six counties in Guangdong, Jiangsu, Henan, Heilongjiang, Sichuan, and Yunnan provinces. County staff linked TB patients identified from facility-specific health and laboratory information systems with TB patients recorded in IDRS and TBIMS. Under-reporting was calculated as the percentage of TB patients not recorded in IDRS or TBIMS. Timeliness, patients recorded within 24 hours after diagnosis, and concordance, accuracy and completeness of key variables when compared to medical records, were analyzed through comparing sampled patient-records with corresponding patient-records in health facilities. Multivariable logistic regression was used to examine factors associated with under-reporting. Results: We found 505 (10.7%) patients diagnosed with TB were missing within IDRS and 1451 (30.9%) patients were missing within TBIMS. Of 171 patient-records reviewed in IDRS and 170 patient-records in TBIMS, 12.3% and 6.5% were found to be untimely, 10.7% and 7.1% were found having inconsistent home address. The risk of under-reporting to both IDRS and TBIMS was greatest in TB diagnosis at a tertiary health facilities and non-residents; the risk of under-reporting to TBIMS was greatest with patients aged 65 or older and extrapulmonary TB (EPTB).Conclusions: We found that more than one in four TB patients were not recorded in TBIMS. It is important to improve the reporting and recording of TB patients. Local TB programs that focus on training, and mentoring high-burden hospitals, facilities that cater to EPTB, and migrant patients may improve reporting and recording. Additional human resources for data collection and management, and monitoring and evaluation systems are needed to improve national surveillance systems and TB prevention, diagnosis and treatment services.

Glycemic Control and the Risk of Tuberculosis: A Population-based Cohort Study

Background: Although diabetes, low body mass index (BMI) and high blood lipid are established risk factors for active tuberculosis, the joint effect of diabetes, BMI and blood lipid is unclear. Methods: We conducted a population-based census in eastern China including 40,311 individuals. We investigated risk factors for incident tuberculosis by excluding tuberculosis at baseline and linking all participants to the Infectious Disease Reporting Management System and Tuberculosis Management Information System of Nanjing City. Follow-up for incident tuberculosis occurred ten years. We matched participants using unique health identity card numbers, name, age, birthdate, and address. We constructed Cox Proportional hazard models adjusting for age, sex, smoking, alcohol use.Results: After ten years follow-up, 143 individuals progressed to tuberculosis. In participants with BMI>24 kg/m2, diagnosed diabetics with fasting blood-glucose (FBG)≥7.0mmol/L showed nearly three-fold increased risk of active TB (HR=3.78, 95%CI: 1.32-10.79, P=0.007), and FBG ≥7.0mmol/L was associated with more than three-fold higher risk of active TB(HR=3.16, 95%CI:1.37-7.28, P=0.007). Among high blood lipid levels, undiagnosed diabetics was related to increase the high risk of TB (HR=3.04, 95%CI: 1.03-8.95, P=0.044) and FBG ≥7.0mmol/L increased nearly two-fold higher risk of TB (HR=2.66, 95%CI: 1.13-6.30, P=0.026). In the linear dose-response analysis, the hazard of TB increased with FBG (with a 1-unit (1-mmol/L) increase in FBG, the hazard of TB increased by 15% (95% CI, 3%–29%). Discussion: In this large population-based cohort study in a medium tuberculosis burden region, we found that diabetes increases the hazard of tuberculosis disease and diabetics with poor glycemic control aggravated this relationship especially in individuals with high level of blood lipid.

Spatiotemporal characteristics and the epidemiology of tuberculosis from 2004 to 2017 in China by the nationwide surveillance system

Background The objective was to identify the Spatial-temporal characteristics and the epidemiology of tuberculosis in China from 2004 to 2017 with Joinpoint regression analysis, Seasonal Autoregressive integrated moving average (SARIMA) model, geographic cluster, and multivariate time series model. Methods The data of TB from January 2004 to December 2017 were obtained from the notifiable infectious disease reporting system supplied by the China CDC. Joinpoint regression analysis was used to observe the trend. The monthly incidence was predicted by the Seasonal autoregressive integrated moving average (SARIMA) model. Spatial autocorrelation analysis was performed to detect geographic clusters. A multivariate time series model was employed to analyze heterogeneous transmission. Results We included 13,991,850 TB cases from 2004 to 2017. The final selected model was the 0 Joinpoint model with an annual average percent change of -3.3. A seasonality was observed across the fourteen years, and the seasonal peaks were in January and March. The best SARIMA model was (0, 1, 1) X (0, 1, 1) 12 , with a minimum AIC (880.5) and SBC (886.4). The predicted value and the original incidence data of 2017 were well matched. The provinces with a high incidence were located in the northwest (Xinjiang, Tibet) and south (Guangxi, Guizhou, Hainan) of China. The autoregressive component had a leading role in the incidence of TB which accounted for 81.5% - 84.5% of the patients on average. The endemic component was about twice as large in the western provinces as the average while the spatial-temporal component was less important there. Most of the high incidences areas were mainly affected by the autoregressive component for the past fourteen years. Conclusion A significant decreasing trend was seen from 2004 to 2017. The seasonal peaks were in January and March every year. Obvious clusters were identified in Tibet and Xinjiang Province. A spatial heterogeneity in the component driving the transmission of TB was identified from the multivariate time series model. This suggested that targeted preventive efforts should be made in different provinces based on the main component contributing to the epidemics.