Economic and health impacts of infectious diseases in China

Abstract Background: A worldwide concern has been raised that novel infectious diseases may outbreak rapidly with a limited response time due to globalization. Severe Acute Respiratory Syndrome, influenza A, Avian Influenza Virus, and Corona Virus Disease 2019 are acute respiratory diseases that have been affected by the movements of people, and globalization accelerates these movements. These infectious diseases not only have an overwhelming health impact but also impact the worldwide economy. Methods: We will conduct a systematic review and meta-analysis in Chinese National Knowledge Infrastructure, WANFANG Database, and the VIP Database for Chinese Technical Periodicals, Web of Science, PubMed, EMBASE, the Cochrane Library, EBSCO host, ProQuest, ProQuest Dissertations & Theses A&I, SAGE Journals, ScienceDirect, JSTOR, and Scopus. We will evaluate the risk of bias of included RCTs according to the criteria and technique proposed in the Cochrane Handbook V.5.1.0 and use ROBINS-I to assess risk of bias in nonrandomized studies. We will use GRADE to evaluate the quality of evidence. Results: Results of this review will be submitted to a peer-reviewed journal. Conclusion: To the best of our knowledge, this study will firstly evaluate both health and economic impact of infectious diseases in china and may provide strategy development ideas for future resistance.


Introduction
With the rapid development of technology, international travelling increases the risk of outbreak of novel infectious disease. Respiratory infectious diseases mainly transmitted by near flying spittle and close-contact which may lead to fast transmission speed and high infection rate. People's lives are threatened when infectious diseases outbreak. Indeed, Infectious diseases cause a significant economic burden and a direct health impact.
China experienced several respiratory epidemics such as Severe Acute Respiratory Syndrome (SARS), influenza A (H1N1), Avian Influenza Virus (H7N9), and Corona Virus Disease 2019  in the past decade. The SARS disaster in 2003 not only leads to serious consequences in China and other infected countries, but also provided precious experience for followed health emergencies. In 2003, SARS spread to 37 countries worldwide. In China, 20 provinces, regions and cities have detected infected cases. [1] The pains from SARS accelerated the development of prevent and control infectious diseases systems in China. Stone suggest that China has taken stricter measures than other countries to defeat H1N1. [2] Then, China responded rapidly and transparently to H7N9 in 2013. [3] Moreover, as of April 14, 2020, COVID-19 spread to 211 countries worldwide. Thirty-one provinces, regions, and cities in China reported infected cases. [4] The response and control measures defeating COVID-19 has been taken quickly and effectively as well.
However, the economic and health impacts of these infectious diseases cannot be neglected. There are previous literatures focus on mortality burden of influenza and find that mortality depends on patients characteristics. [5,6] Also, a previous systematic review and meta-analysis research the economic burden of influenza as well. [7] Moreover, there is systematic review focus on the prevalence of human influenza in other countries. [6,[8][9][10][11] Pasquini-Descomps evaluates the cost-effectiveness to H1N1. [12] Crawford et al reviews global health response to HIV/AIDS, SARS, H1N1, and Ebola. [10] To the best of our knowledge, no previous systematic review or meta-analysis comprehensively studied both economic and health impact of infectious diseases in China. Besides, there is no systematic review summarized all papers discussed SARS, H1N1, H7N9, and COVID-19.
Hence, this protocol focused on both economic and health impact of infectious diseases in China. We especially focused on 4 infectious diseases which outbreak in China: SARS, H1N1, H7N9, and COVID-19. We expanded the inclusion criteria to include more related articles and also considered effectiveness of economic costs for infectious diseases.

Design and registration
In order to synthesise combinable research evidence, this protocol follows reporting items for systematic review and meta-analysis protocols. [13] This protocol has been registered on PROSPERO (CRD42020173845).

Data extraction
This study will use Endnote X7 (Clarivate Analytics, London, United Kingdom www.clarivate.com) to manage retrieved records. Fan and Li will screen the title and abstract independently. Then, we will access the full articles of selected articles and screened for further assessment. The disagreements between those 2 authors will be discussed by a third author. The data will be extracted from selected articles by 2 independent reviewers and formed using Microsoft Excel 2016. The details include descriptive characteristic (title, author, year of publication, published journal, region of research, analytical method, type of infectious diseases, data source, year of sample, and short description of findings) population characteristics (number of participates, participates characteristic) and outcome variables.

Risk of bias
Two reviewers will evaluate the risk of bias of included RCTs according to the criteria and technique proposed in the Cochrane Handbook V.5.1.0, [14] which including random sequence generation, allocation concealment (selection bias), blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting, and other bias.
The risk of bias will be evaluated according to the tool for assessing risk of bias in nonrandomized studies of interventions (ROBINS-I), [15] including bias due to confounding, bias in selection of participants into the study, bias in classification of intervention, bias due to deviations from intended interventions, bias due to missing data, bias in measurement of outcomes, bias in selection of the reported result, and overall risk of bias. We will evaluate methodological quality as low, moderate, high risk of bias and no information.

Evidence quality
The Grades of Recommendation, Assessment, Development and Evaluation (GRADE) approach will be used to assess the quality of evidence for the main outcomes. [16] According to GRADE, quality of evidence classified into 4 levels: high, moderate, low, and very low. There are 5 factors (risk of bias, indirectness, inconsistency, publication bias, and inaccuracy) may degrade the quality of evidence and 3 factors may improve the quality of evidence. The conflict will be discussed by an independent author.

Data synthesis
We will use Excel 2016 to summarize the data of all the included studies and manage their characteristics and data related to this systematic review and meta-analysis. This study will use Stata 15.1 (StataCorp, TX, USA, www.stata.com) to analyze the economic and health impacts of infectious diseases in China. Odds ratios (ORs) and Standardized mean difference (SMD) will be used as effect size in this study. Then, this study will report the Li et al. Medicine (2020) 99:30 Medicine d-value and the Confidence interval for effect size (95% CI) of included studies. The heterogeneity of each meta-analysis is tested by I 2 statistics. A low P value of x 2 test and a high I 2 value represent heterogeneity.

Subgroup and publication bias
For considerable heterogeneity studies, this study will adopt subgroup analysis and sensitivity analysis. Considering the publication bias, this study will draw a funnel plot by using Begg's and Egger's methods as well. [17,18]