The epidemiological trends of 45 national notifiable infectious diseases in China: An analysis of national surveillance data from 2013 to 2022

The epidemiological trends of 45 national notifiable infectious diseases in China: An analysis of national surveillance data from 2013 to 2022 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The epidemiological trends of 45 national notifiable infectious diseases in China: An analysis of national surveillance data from 2013 to 2022 Hongrang Zhou, Xiaoling Wang, Guifu Li, Zhe Zhou, Xiaoming Wang, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3860619/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective To conduct an in-depth analysis of the epidemiological characteristics of 45 notifiable infectious diseases in mainland China the past decade, in order to comprehensively understand and grasp the epidemic situation, as well as to provide references and foundations for the development of effective prevention and control strategies and measures. Method Based on the monthly analysis report of the National Infectious Disease Surveillance System (NIDSS), data on reportable infectious diseases in China from 2013 to 2022 were obtained. The data were processed using IBM SPSS 22.0 and Excel 2010 software, and a joint-point regression model was used to analyze incidence and case-fatality ratios trends from 2013 to 2022. Results From 2013 to 2022, a total of 76,874,318 cases of notifiable infectious diseases were reported in mainland China, with an average annualized incidence rate of 551.26/100,000, and 207,216 deaths from notifiable infectious diseases, corresponding to an average annualized case-fatality rate of 2.70 /1,000. Throughout this period, the overall incidence rate showed a downward trend, with an average annual percentage changes (AAPC) of -0.14% (95% CI: -3.75–3.51%), while the overall case-fatality rate showed an upward trend, with an AAPC of 5.41% (95% CI: 2.29–8.61%). In this decade, HFMD, hepatitis B, infectious diarrhea, tuberculosis, and influenza were the prevalent infectious diseases in terms of morbidity among 45 notifiable infectious diseases, while acquired immune deficiency syndrome (AIDS), tuberculosis, rabies, infectious diarrhea, and COVID-19 were the diseases with high numbers of deaths. According to the classification of A, B and C, the incidence of notifiable infectious diseases in mainland China from 2013 to 2022 was primarily dominated by C infectious diseases, accounting for 54.50%. Based on different transmission routes, intestinal infectious diseases were the most prevalent, accounting for 40.64% of the total morbidity. The overall monthly incidence trend of notifiable infectious diseases in mainland China exhibited a "W" distribution, while the monthly case-fatality ratios trend shows a "M" distribution. During the COVID-19 epidemic period (2020–2022), compared with the pre-epidemic period (2017–2019), the incidence rate of 6 infectious diseases increased and the incidence rate of 34 infectious diseases decreased; the case-fatality ratios of 18 diseases increased and 14 diseases decreased. Conclusion It is very crucial to continuously reinforce the prevention and control of key infectious diseases, including AIDS, tuberculosis and viral hepatitis as well as highly prevalent infectious diseases, such as hand-foot-mouth disease, influenza and infectious diarrhoeal diseases. Concurrently, we should enhance our surveillance and response to emerging infectious diseases to safeguard public health and safety. Figures Figure 1 Figure 2 Figure 3 Introduction With the changes in ecological environment and human behavior, the emergence of new infectious diseases and the resurgence of established infectious diseases have led to new threats to human beings[ 1 – 4 ]. Since the 21st century, with the improvement of sanitary conditions and nutritional status of the populations, the development of diagnostic and therapeutic techniques, vaccines and drugs have been adopted[ 5 – 8 ]. Most infectious diseases have been effectively controlled and some had even been eliminated[ 9 ]. Nonetheless, with the economic growth and urbanization acceleration,, the prevention and control of infectious diseases did not further strengthen correspondingly, leading to the resurgence and epidemic of traditional infectious diseases like tuberculosis. Simultaneously, novel infectious diseases have emerged due to increased international exchanges and ecological environment changes, such as SARS[ 10 ], poliomyelitis[ 11 ], pandemic H1N1 influenza[ 12 ], avian influenza A H5N1, avian influenza A H7N9[ 13 ] and COVID-19[ 14 – 16 ]. These emerging infectious diseases not only impose a significant economic burden on China but also pose a grave threat to public life safety[ 17 ]. To effectively prevent and control infectious diseases, the China has implemented a series of measures, including shifting from non-synergistic to cooperative, multi-sectoral, and One Health integrated prevention and control strategies[ 18 , 19 ]. Through interdisciplinary collaboration and combined prevention and treatment, our country has achieved remarkable achievements in the prevention and treatment of infectious diseases. Infectious disease surveillance is a crucial public health monitoring assignment which not only requires a long-term continuously, but also requires an in-depth comprehension of the epidemiological patterns of infectious diseases and assessment of the effects of the interventions. China has established a national standardized reporting system for notifiable infectious diseases in the 1950s[ 9 ] and an Internet-based case reporting system in 2003[ 20 ], which has provided strong support for the prevention and control of infectious diseases. In this investigation, we extracted epidemic data reported by the National Infectious Disease Surveillance System (NIDSS) in mainland China (excluding Hong Kong, Macao, and Taiwan) from 2013 to 2022, including the relevant data during the COVID-19 epidemic. Through analyzing the epidemiological characteristics and trends of infectious diseases in past ten years across the country, we try to further explore and understand the epidemiological patterns of infectious diseases, evaluate the situation of epidemics, and provide references and bases for the formulation of strategies and measures for the prevention and control of infectious diseases. Methods Data sources The data come from the monthly analysis report of the NIDSS from 2013 to 2022, which was reported by the Division of Infectious Disease, Chinese Center for Disease Control and Prevention. The data includes the numbers of cases and deaths per month. The annual population data for the years from 2013 to 2022 were collected from the data published on the website of the Chinese National Bureau of Statistics. Procedures China established a system of routine reporting on notifiable infectious diseases in the 1950s. The system currently covers data from 31 provinces in mainland China, with a coverage of approximately 1.4 billion people. This system has been updated web-based since 2003 and operated through administrative grading responsibility and territorial management. The number of notifiable infectious diseases included in the reporting system is increasing from 18 before 1978 to 40 after 2020[ 2 , 9 , 21 ], as shown in Table 1 . Table 1 Changes to the list of notifiable diseases in China, 1955–2022 Year No. of diseases No. of the different classes of the diseases (including newly added ) Cancel-reporting A B C 1955 18 3 (Plague, cholera, smallpox) 15 (Epidemic encephalitis B, diphtheria, scrubtyphus, relapsing fever, dysentery, typhoid fever, scarlet fever, epidemic cerebrospinal meningitis, measles, poliomyelitis, pertussis, anthrax, undulant fever, forest encephalitis and rabies) None None 1978 25 3 22 (Influenza, viral hepatitis # , tsutsugamushi disease, epidemic haemorrhagic fever, leptospirosis, brucellosis, malaria) None None 1989 35 2 22 ( HIV/AIDS, gonorrhea, syphilis, kala-azar, dengue fever) 11 (Epidemic encephalitis B, tuberculosis, schistosomiasis, filariasis, echinococcosis, lepra, epidemic parotitis, rubella, neonatal tetanus, acute hemorrhagic conjunctivitis, other infectious diarrhea*) 5 (Smallpox, relapsing fever, forest encephalitis, Tsutsugamushi disease, undulant fever) 2004 37 2 25 (Tuberculosis, schistosomiasis, neonatal tetanus, SARS and highly pathogenic avian influenza A H5N1) 10 (Scrubtyphus and kala-azar) None 2008 38 2 25 11 (Hand, foot and mouth disease) None 2009 39 2 26 (Influenza A H1N1) 11 None 2013 39 2 26 (H7N9 avian influenza) 11 Influenza A H1N1 2020 40 2 27 (COVID-19) 11 None #Viral hepatitis consists of six types: hepatitis A, hepatitis B, hepatitis C, hepatitis D, hepatitis E, and unclassified hepatitis. And hepatitis D has been included in the Communicable Disease Report since 2016. *Other infectious diarrhea refers to diarrhea other than that caused by cholera, dysentery or typhoid fever. According to the “Law of the People's Republic of China on Prevention and Control of Infectious Diseases”, the notifiable infectious diseases are classified into classes A, B and C. Among them, there are 2 in type A, 27 in type B, and 11 in type C[ 22 ] (Supplementary S1). And Influenza A H1N1 was only reported in 2009–2013, as H1N1 was included in the monitoring of influenza viruses in 2014, this study combined the H1N1 influenza data with those of other influenza viruses for statistical analysis[ 20 ]. In addition, viral hepatitis was subdivided into hepatitis A, B, C, D, E and unclassified. In this study, we analyzed the data strictly according to the classification criteria of notifiable infectious diseases. Statistical analysis Yearly incidence (per 100000) was the number of reported cases per year divided by the mid-year population size. The fatality rate (per 1000) was the number of reported deaths divided by the number of reported cases over the same period[ 20 ]. In addition, radar charts based on the percentage of patients per month to characterize the distribution of the diseases throughout the year were applied. Microsoft Excel 2010 (Microsoft, Redmond, WA, USA) was utilized for data extraction, sorting and cleaning. The joinpoint regression models[ 23 , 24 ] were used to examine incidence and case-fatality rate trends from 2013 to 2022 and to identify changes in trends at every stage. The software Joinpoint Regression Program Version 5.0.2 (Statistical Research and Applications Branch, National Cancer Institute) was employed to build the joinpoint regression models, calculate annual percentage changes (APC) and average annual percentage changes (AAPC) to express trends. If the point of joinpoint regression models is zero, then AAPC = APC, and when APC > 0, it indicates an upward trend; when APC < 0, it indicates a downward trend, when APC = 0, it indicates a steady state[ 2 , 20 , 22 ]. We also calculated 95% confidence intervals for APCs and AAPCs and tested hypotheses using Z test with P < 0.05 as the significance level. Results Overall incidence and case-fatality ratios This study covered 45 infectious diseases during the period from 2013 to 2022. In this 10-year period, the total number of reported cases of infectious diseases amounted to 76,874,318, with an average annual incidence rate of 551.26/100,000. HFMD, hepatitis B, infectious diarrhea, tuberculosis, and influenza were the five diseases with the highest average annual incidence rates for this period, as shown in Fig. 1 A (Supplementary Table S1 ). Among the 76,874,318 cases of infectious disease, 207,216 deaths were recorded, representing an average yearly case-fatality ratio of 2.70 deaths per 1000 cases per year. AIDS, tuberculosis, infectious diarrhea, COVID-19, and hepatitis C account for the highest mortality rates,, while rabies, H5N1 influenza, plague, H7N9 influenza, and AIDS have the highest case-fatality ratios, as depicted in Fig. 1 B (Supplementary Table S1 ). From 2013 to 2019, the annual incidence rate of the total disease continued to rise by a staggering 48.83%, and this trend was confirmed by the number of cases. In the following period from 2020 to 2022, although the annual incidence rate of the overall disease has declined, it still shows an increasing trend in this period, as shown in Fig. 1 C (Supplementary Table S2). Meanwhile, the rate of deaths from diseases in general was also increasing during the period from 2013 to 2022, which is consistent with the trend in the number of disease deaths. It is interesting to realize that the number of disease deaths showed no significant fluctuation or even a slight decrease during the epidemic of COVID-19, but the rate of disease deaths showed a relatively large increase, as shown in Fig. 1 D (Supplementary Table S2). Epidemic trend of 45 infectious diseases stratified by A, B and C According to official statistical data, from 2013 to 2022, the incidence of notifiable infectious diseases in mainland China was dominated by type C infectious diseases, which accounted for 54.50% of the total number of cases, and the incidence of type B infectious diseases accounted for 45.498%, while the incidence of type A infectious diseases was much lower than 0.01% (Supplementary Figure S1 , Tables S3 and S4). The total incidence of the three types of infectious diseases decreased during this period, with an AAPC of -0.14% (95% CI: -3.75–3.51%). However, the case-fatality ratio of the diseases showed an increasing trend, with an AAPC of 5.41% (95% CI: 2.29–8.61%). Among them, the incidence rates of both type A and B infectious diseases showed a decreasing trend, with AAPCs of -8.69% (95% CI: -22.78 to 7.63%) and − 1.67% (95% CI༚-2.51 to -0.82%), respectively. But the case-fatality rates of both were on the rise, with AAPCs of 5.22% (95% CI༚-10.74 to 22.69%) and 7.33% (95% CI༚-4.82 to 9.85%), respectively. In contradistinction to infectious diseases of type A and B, the incidence of infectious diseases of type C showed an increasing trend, with an AAPC of 1.14% (95% CI: -5.29 to 7.84%). The case-fatality rate for type C infectious diseases, however, showed a decreasing trend, with an AAPC of -28.44% (95% CI: -41.69 to -8.04%). Additionally, the data of three years before and after the COVID-19 outbreak were carefully analysed in this study for comparison (Supplementary Table S5). According to the analysis, the total average annual incidence rate during the outbreak period (2020–2022) decreased compared with the pre-outbreak period (2017–2019), with a decrease of 23.32%. The incidence rates of infectious diseases in type A, B, and C have decreased, with the most significant decrease in type C infectious diseases at 31.27%. In terms of case-fatality rate, however, the performance was the opposite of the incidence rate, with an increase of 38.77%. In particular, the case-fatality rate of infectious diseases of type A and B increased by 137.04% and 21.53%, while the case-fatality rate of infectious diseases of type C decreased by 55.65%, as shown in Table 2 . Table 2 Annual percentage change in incidence and case-fatality ratios of 45 infectious diseases stratified by A, B and C, from 2013 to 2022 Types Yearly incidence rate (per 100 000) Case-fatality ratios (per 1000) Duration APC% (95% CI) AAPC % (95% CI) 2017-2019VS 2020–2022(%) Duration APC% (95% CI) AAPC % (95% CI) 2017-2019VS 2020–2022(%) A 2013–2022 -8.69 (-22.78 to 7.63) -8.69 (-22.78 to 7.63) -16.20 2013–2022 5.22 (-10.74 to 22.69) 5.22 (-10.74 to 22.69) 137.04 B 2013–2022 -1.67* (-2.51 to -0.82) -1.67* (-2.51 to -0.82) -11.76 2013–2022 7.33* (4.82 to 9.85) 7.33* (4.82 to 9.85) 21.53 C 2013–2022 1.14 (-5.29 to 7.84) 1.14 (-5.29 to 7.84) -31.27 2013–2020 -14.68 (-49.59 to 152.27) -28.44* (-41.69 to -8.04) -55.65 2020–2022 -61.34* (-86.59 to -4.59) Total 2013–2022 -0.14 (-3.75 to 3.51) -0.14 (-3.75 to 3.51) -23.32 2013–2022 5.41* (2.29 to 8.61) 5.41* (2.29 to 8.61) 38.77 APC, annual percent change; AAPC, average annual percent change. * p < 0.05 Epidemic trend of 45 infectious diseases in different transmission routes As shown in Fig. 2 A and B (Supplementary Table S6 and S7), we can observe that during the period from 2013 to 2022, notifiable infectious diseases in mainland China are predominantly characterized by intestinal infectious diseases, accounting for 40.64% of the total number of cases. Respiratory infectious diseases and sexual, blood and mother-to-child borne infectious diseases also occupy a considerable proportion, accounting for 30.82% and 26.90%. However, zoonotic, vector borne and other (contact) infections represented less than 1.00% of the total. In terms of deaths from related diseases, sexual, blood and mother-to-child borne of infectious diseases were the main contributors, accounting for 83.19% of the total number of deaths. Respiratory and zoonotic infectious diseases also accounted for a certain proportion, accounting for 12.49% and 3.08%. Similarly, intestinal, vector borne and other (contact) infections accounted for less than 1.00% of deaths. Trends in the incidence and case-fatality rates of the various infectious diseases showed varying trends over the past decade. The incidence rates of the intestinal, sexual, blood and mother-to-child borne, and other (contact) infections diseases showed an increasing trend, with AAPCs of 6.27% (95% CI: -1.47 to 14.44), 1.26% (95% CI: -2.47 to 4.21), and 0.87% (95% CI: -0.64 to 2.53). In terms of case-fatality rates, there was an increasing trend for intestinal and other (contact) infections diseases, while there was a decreasing trend for sexual, blood and mother-to-child borne, with AAPCs of 0.60% (95% CI: -8.35 to 10.42) and 4.29% (95% CI: 3.44 to 5.01), and − 21.32% (95% CI: -25.84 to − 16.76). Respiratory, zoonotic and vector borne types of infectious diseases showed a decreasing trend, with AAPCs of -6.81% (95% CI: -11.14 to -2.07), -19.65% (95% CI: -33.41 to -3.52), and − 5.89% (95% CI: -12.32 to -0.61). Regarding case-fatality rates, all of them also showed a decreasing trend, with AAPCs of -22.61% (95% CI: -30.24 to -14.26), -1.58% (95% CI: -19.89 to 21.02) and − 21.72% (95% CI: -25.81 to -15.14), as shown in Table 3 (Supplementary Tables S8). Table 3 Annual percentage change in incidence and case-fatality ratios of 45 infectious diseases stratified by different transmission routes, from 2013 to 2022. Types Yearly incidence rate (per 100 000) Case-fatality ratios (per 1000) Duration APC% (95% CI) AAPC % (95% CI) 2017-2019VS 2020–2022(%) Duration APC% (95% CI) AAPC % (95% CI) 2017-2019VS 2020–2022(%) Intestinal 2013–2022 6.27 (-1.47 to 14.44) 6.27 (-1.47 to 14.44) -39.57 2013–2022 0.60 (-8.35 to 10.42) 0.60 (-8.35 to 10.42) -33.33 Respiratory 2013–2018 1.24 (-5.53 to 27.41) -6.81* (-11.14 to -2.07) -17.73 2013–2022 -22.61* (-30.24 to -14.26) -22.61* (-30.24 to -14.26) 87.18 2018–2022 -15.97* (-34.34 to -7.98) Sexual, blood and mother-to- child borne 2013–2019 -3.93 (-17.59 to 1.49) 1.26 (-2.47 to 4.21) -4.94 2013–2017 -7.85 (-17.44 to 18.07) -21.32* (-25.84 to -16.76) 9.27 2019–2022 12.50 (-0.44 to 33.95) 2017–2022 -30.66* ( -43.93 to -25.05) Zoonotic 2013–2022 -19.65* (-33.41 to -3.52) -19.65* (-33.41 to -3.52) 25.96 2013–2022 -1.58 (-19.89 to 21.02) -1.58 (-19.89 to 21.02) -70.69 Other (contact) 2013–2019 2.59* (0.08 to 10.14) 0.87 (-0.64 to 2.53) -31.83 2013–2016 3.82 (-0.18 to 6.40) 4.29* (3.44 to 5.01) -33.33 2016–2019 9.18* (6.42 to 11.47) 2019–2022 -2.49 (-10.37 to 1.90) 2019–2022 0.07 (-4.06 to 2.50) Vector borne 2013–2015 19.02 (-10.05 to 57.13) -5.89* (-12.32 to -0.61) -80.56 2013–2015 -57.01* (-66.69 to -32.27) -21.72* (-25.81 to -15.14) -38.55 2015–2022 -12.00* (-32.63 to -3.2) 2015–2022 -7.10 (-13.31 to 10.16) Total 2013–2022 -0.14 (-3.75 to 3.51) -0.14 (-3.75 to 3.51) -23.17 2013–2022 5.41* (2.29 to 8.61) 5.41* (2.29 to 8.61) 38.77 APC, annual percent change; AAPC, average annual percent change. * p < 0.05 In accordance with the results of the study, the average annual incidence rates of infectious diseases spread by all routes excluding zoonotic infectious diseases decreased during the epidemic, compared with the average of the three years preceding the COVID-19 epidemic (Supplementary Tables S8). Vector borne infectious diseases showed the greatest decrease, with a decrease of 80.56%, followed by intestinal infectious diseases, with a decrease of 39.57%. As for the case-fatality rate, the average annual case-fatality rates of infectious diseases through intestinal, zoonotic, vector borne and other (contact) infectious diseases during the epidemic were lower than those before the epidemic. Of these, infectious diseases of zoonoti showed the highest decrease, by 70.69%, followed by vector borne with a decrease of 38.55%. Respiratory and sexual, blood and mother-to-child borne diseases were both higher during the COVID-19 epidemic than before the epidemic, with rises of 87.18% and 9.27%, respectively. Seasonal distribution of infectious diseases. As Fig. 3 A shows (Supplementary Table S9), the total monthly incidence trend of notifiable infectious diseases in mainland China shows a "W" distribution from 2013 to 2022, including the monthly incidence trend in the three years before and during the COVID-19 epidemic. It should be emphasized that although the monthly incidence rates in the three years before the COVID-19 epidemic were higher than those in the 2013–2022 period, the monthly incidence rates during the COVID-19 epidemic were lower than those in the 2013–2022 period (except for January). Compared with the 3 years prior to the COVID-19 epidemic and the 2013–2022 period, the monthly case fatality rates during the epidemic were higher than the former two except for January and November. Based on the calculation of the average seasonal index for each month of notifiable infectious disease incidence in mainland China from 2013 to 2022, the results showed that the seasonal indexes for January, May through July, and December were 1.08, 1.15, 1.31, 1.23, and 1.07, respectively, which indicated that the number of cases in these months was higher than the average for the whole year, as shown in Fig. 3 B. The seasonal index for case-fatalities was 1.03, 1.07, 1.15 and 1.30 for the months of August-September and November-December respectively, indicating that the number of case-fatalities in these months was higher than the average, as shown in Fig. 3 C. Meanwhile, this study utilized radar charts to provide insights into the monthly incidence and monthly case-fatality trends of each infectious disease. As for monthly incidence rates, 9 infectious diseases showed significant seasonal characteristics, 19 infectious diseases showed aggregated seasonal characteristics, and 15 infectious diseases showed no significant seasonal characteristics. With respect to monthly case-fatality rates, 11 infectious diseases showed significant seasonal characteristics, 22 infectious diseases exhibited aggregated seasonal characteristics, while no significant seasonal characteristics were observed for 6 infectious diseases (Supplementary Figure S2). Trends in incidence and case-fatality ratios for 45 infectious diseases Table 4 shows that from 2013 to 2022, the incidence of 7 out of 45 infectious diseases, including HIV, pertussis, diphtheria, syphilis, brucellosis, influenza, and scarlet fever, showed a significant upward trend. Specifically, pertussis and influenza had fastest increasing rates, with AAPCs of 25.90% (95% CI: 12.13 to 54.64) and 43.83% (95% CI: 24.48 to 168.87). Simultaneously, the incidence rates of 22 infectious diseases showed a significant downward trend, with the fastest decreases in schistosomiasis, mumps, rubella and neonatal tetanus, with AAPCs of -44.53% (95% CI: -77.12 to -32.19), -40.72% (95% CI: -59.40 to -36.92), -34.11% (95% CI: -63.66 to -23.81) and − 31.81% (95% CI: -36.28 to -29.62). And 4 of the 45 infectious diseases showed a significant upward trend in case-fatality rates during this period, including HIV, tuberculosis, scarlet fever, and rubella. Of particular note, rubella and scarlet fever showed a fastest increases, with AAPCs of 237.87% (95% CI: 223.08 to 3030.81) and 37.41% (95% CI: 16.00 to 102.81). In addition, 10 infectious diseases showed significant decreases in case-fatality rates. Among them, typhus, cholera, and schistosomiasis showed a fastest rate of decline, with AAPCs of -63.33% (95% CI: -88.13 to -63.63), -44.50% (95% CI: -58.39 to -37.06) and − 37.23% (95% CI: -78.49 to -27.01). Table 4 Annual percentage change in incidence of 45 infectious diseases, from 2013 to 2022 Items Yearly incidence† Case-fatality ratios† Comparison of the incidence and fatality ratios in the three years before and after the COVID-19 outbreak (2017–2019 vs 2020–2022)༈%༉ AAPC (95% CI) /% AAPC (95% CI) /% Yearly incidence Case-fatality ratios Plague -13.39* ( -44.72 to -4.41) -8.42 (-20.76 to 5.39) 15.87 71.43 Cholera -8.13 (-23.62 to 5.16) -44.50* (-58.39 to -37.06) -19.52 — SARS-CoV — — — — AIDS 1.93* (1.00 to 2.85) 3.58* (2.99 to 4.26) -10.99 16.51 Hepatitis A -9.46* (-12.65 to -6.87) -3.17 (-11.11 to 2.41) -31.67 -21.74 Hepatitis B 0.96 (-0.50 to 2.51) -5.46* (-7.44 to -3.51) -2.93 -3.77 Hepatitis C -0.19 (-1.17 to 0.81) 5.58 (-0.66 to 10.65) -8.84 45.16 Hepatitis D -13.35* (-18.36 to -8.55) — -44.23 — Hepatitis E -1.78 (-4.69 to 1.18) -2.57 (-9.13 to 3.77) -17.90 -22.83 Other hepatitis -17.79* (-19.92 to -16.64) -3.68 (-11.87 to 0.82) -51.01 102.74 Poliomyelitis — — — — H5N1 -5.00 (-15.46 to 2.94) -3.93 (-18.94 to 14.68) — — Measles -40.72* (-59.40 to -36.92) -5.71 (-25.93 to 13.91) -78.88 -100.00 EHF -5.77* (-10.15 to -1.71) -2.60 (-11.49 to 5.97) -31.56 7.07 Rabies -22.52* (-24.72 to -21.54) -0.22 (-2.64 to 1.27) -59.84 -8.40 Epidemic encephalitis B -29.34* (-42.77 to -24.39) -10.81* (-29.69 to -3.54) -80.63 -62.48 Dengue -17.27 (-43.27 to 2.98) -6.30 (-11.73 to 8.07) -95.84 -100.00 Anthrax 3.05 (-2.20 to 8.93) -4.26 (-19.10 to 12.42) -3.41 -54.30 Dysentery -16.75* (-18.59 to -15.72) -1.84 (-22.39 to 13.91) -49.39 120.76 Tuberculosis -6.55* (-7.50 to -5.75) 14.33* (7.00 to 20.26) -26.59 41.08 TF&PF -9.45* (-12.51 to -7.25) 8.62 (-10.81 to 32.29) -36.60 95.82 Meningococcal meningitis -12.53* (-17.56 to -8.61) -3.35 (-11.11 to 2.38) -49.32 -27.21 Pertussis 25.90* (12.13 to 54.64) -23.36 (-43.34 to 1.98) -15.95 18.17 Diphtheria 6.30* (0.03 to 46.95) — 297.27 — Neonatal tetanus -31.81* (-36.28 to -29.62) 0.42 (-19.41 to 15.72) -69.62 -18.27 Scarlet fever -11.38* (-21.39 to -3.80) 37.41* (16.00 to 102.81) -71.58 — Brucellosis 4.78* (1.35 to 9.71) 3.88 (-8.06 to 19.87) 51.14 -17.86 Gonorrhea 1.39 (-3.43 to 6.18) 12.34 (-5.10 to 42.25) -15.85 254.08 Syphilis 1.65* (0.28 to 2.98) -5.04 (-11.50 to 1.28) -4.97 9.64 Leptospirosis -5.51 (-13.97 to 2.22) -11.71* (-24.05 to -4.81) 48.04 151.58 Schistosomiasis -44.53* (-77.12 to -32.19) -37.23* (-78.49 to -27.01) -96.86 — Malaria -18.31* (-24.96 to -14.58) -1.12 (-12.66 to 7.37) -65.44 43.68 H7N9 32.00 (-16.56 to 132.08) -0.01 (-12.39 to 16.45) -100.00 — COVID-19 — — — — Influenza 43.83* (24.48 to 168.87) -34.77* (-61.63 to -3.11) -8.42 -63.03 Mumps -13.74* (-19.83 to -9.56) 7.14 (-11.41 to 25.12) -56.75 588.96 Rubella -34.11* (-63.66 to -23.81) 237.87* (223.08 to 3030.81) -86.76 650.30 AHC -4.61* (-9.20 to -0.26) -11.36 (-75.45 to 25.88) -27.82 175.19 Leprosy -11.28* (-13.29 to -9.68) -3.53* (-7.10 to -0.04) -32.82 47.85 Typhus -4.76* (-6.02 to -3.57) -63.33* (-88.13 to -63.63) 21.38 — Kala azar 4.67* (1.81 to 8.49) -2.61 (-6.69 to 2.90) 28.80 — Echinococcosis -3.33 (-6.99 to 0.15) -0.20 (-10.68 to 9.93) -41.30 26.90 Filariasis -0.66 (-3.91 to 2.54) — — — Infectious diarrhea 1.46 (-3.22 to 6.87) -14.70* (-21.59 to -9.15) -14.53 -62.88 HFMD -11.19* (-21.75 to -3.43) -32.30* (-50.38 to -23.60) -55.30 -74.20 †When the number of cases or deaths data contained zero, we substitute 1‰ for zero to calculate the incidence and case-fatality rates. APC, annual percent change; AAPC, average annual percent change. * p < 0.05 When comparing the average annual incidence rates of infectious diseases before and during the COVID-19 epidemic, we found that the incidence rates of 6 infectious diseases increased during the epidemic compared with the pre-epidemic period, among which diphtheria, brucellosis, and leptospirosis showed the most significant increases, reaching 297.27%, 51.14%, and 48.04%, respectively. The incidence rates of 34 infectious diseases declined, with H7N9, schistosomiasis, dengue fever, and rubella showing the most significant decreases of 100%, 96.86%, 95.84%, and 86.76%, respectively. In terms of case-fatality rates, we found an increase in 18 diseases, with rubella, mumps, gonorrhea and AHC showing the most significant increases, reaching 650.30%, 588.96%, 254.08% and 175.19%, respectively. There were 14 diseases that showed decreases, with measles, dengue fever, HFMD and influenza showing the most significant decreases, dropping 100%, 100%, 74.20% and 63.03%, respectively. Discussion According to research findings over the years[ 2 , 20 , 25 – 27 ], infectious diseases have been closely associated with the development of society in the 21st century, and their incidence and deaths have continued to increase, posing a serious threat to people's health. After the 2003 SARS outbreak, the State Council of the People's Republic of China proposed the 2003 Emergency Regulations for Public Health Emergencies[ 27 ]. Subsequently, the Law of the People's Republic of China on prevention and control of infectious diseases was revised in 2004 and 2013, respectively[ 27 , 28 ]. With a variety of strategies to prevent the spread of infectious diseases implemented[ 18 , 19 ], including improved safety of blood collection, large-scale vector control, and enhanced screening for early monitoring and warning, etc, there were huge achievements in the prevention and control of infectious diseases including the elimination of filariasis in 2006, neonatal tetanus in 2012, and malaria in 2021, etc[ 29 – 31 ]. However, the outbreaks and epidemics of emerging infectious diseases, such as COVID-19, have still posed new challenges to infectious disease prevention and control and in public health. In this study, the incidence of reportable diseases and the case-fatality rate show a gradual upward trend during the period from 2013 to 2019, especially the case-fatality rate. The trend is mainly attributed to the following reasons. First, with the increase in people's awareness of health, there is also an increase in attention to all types of diseases. This means that people pay more attention to the prevention, diagnosis and treatment of diseases, which promotes the rise of disease incidence. Secondly, the improvement in the level of diagnosis of infections has also contributed to the increase in incidence[ 32 ]. In addition, the threat of infection continues to increase with rising antimicrobial resistance, increased population mobility, changing human behavior and the emergence and spread of new infectious diseases[ 20 ]. During the COVID-19 epidemic (2020 to 2022), most infectious disease incidence levels showed a greater decline, which may be related to the effectiveness of non-pharmacological interventions[ 33 ], such as since the outbreak of COVID-19, countries around the world have taken measures to control the development of the epidemic, including the wearing of face-masks, washing hands frequently, and isolation and control. These measures have played a role in preventing and controlling the spread of other pathogens, especially respiratory infections, while curbing the spread of the COVID-19 epidemic[ 34 , 35 ]. It is also taken into account that the surveillance of other infectious diseases declined after the COVID-19 outbreak, which may have led to a decrease in the number of reported cases of other infectious diseases[ 36 , 37 ]. In most infectious diseases, however, there was an increasing trend in case-fatality rates during this period, although the number of deaths from the corresponding diseases declined, and the main reason for this trend was mainly due to a decrease in the number of incidence cases. Of course, there are also a few diseases in which the number of deaths has risen, such as syphilis. This may be related to the fact that some patients were unable to receive timely medical care due to shyness, and the possibility cannot be ruled out that the treatment and resuscitation of some patients was untimely or inadequate due to the constraints and inadequacy of medical resources during the COVID-19 epidemic. From the perspective of the disease spectrum, the incidence and death of notifiable infectious diseases in China show a more concentrated trend. The top five diseases with the highest incidence rates, such as hand-foot-mouth disease, influenza, dysentery, viral hepatitis and tuberculosis, accounted for 79.88 per cent of the total number of incidence cases, demonstrating the seriousness of these diseases in our country's infectious diseases. At the same time, the top five diseases with the highest case fatality rates of AIDS, tuberculosis, dysentery, viral hepatitis and influenza accounted for 96.56% of all deaths, which also highlights the lethality of these diseases. The incidence and case fatality rates of AIDS have been on the rise in recent decades, although China has implemented policies to strengthen AIDS publicity and education, prevention and intervention, and testing and treatment[ 38 , 39 ], which have effectively reduced the risk of transmission and fatality of AIDS, the situation of AIDS prevention and control is still serious. In our country, sexual transmission has become the main transmission route of AIDS, and we should continue to strengthen the monitoring of AIDS patients in the future, as well as strongly carry out the promotion of AIDS prevention and treatment knowledge and advocate safety behaviors[ 40 ]. The incidence of tuberculosis shows a significant downward trend from 2013 to 2022, which is mainly attributed to the comprehensive coverage of the direct supervision short-course chemotherapy strategy and the implementation of a series of tuberculosis prevention and treatment plans[ 41 ], but the decline during the COVID-19 epidemic may be related to the failure to provide timely diagnosis and treatment as a result of epidemic prevention and control. The effectiveness of tuberculosis prevention and control in China still has a gap with the World Health Organization's goal of ending tuberculosis by 2035, and in the future it will be necessary to strengthen focused prevention and control in areas with high incidence of tuberculosis and in the main susceptible population groups. The incidence rates of viral hepatitis (except hepatitis B) are showing a decreasing trend, and the case fatality rates (except hepatitis C) are also showing a decreasing trend. Unfortunately, the prevalence of viral hepatitis in China is still large, especially for chronic hepatitis B and C[ 42 , 43 ], so we need to further strengthen the screening and antiviral treatment for hepatitis B and C patients. In recent years, the average incidence of C infectious diseases has been on the rise, despite a 31.27% decrease during the COVID-19 epidemic compared with the three years prior to the epidemic, which was mainly caused by the high incidence of HFMD, infectious diarrheal, and influenza. Among them, the incidence of HFMD is dominated by children under 5 years of age, which requires the dissemination of knowledge about HFMD prevention and treatment to parents and teachers, as well as the reinforcement of vaccination[ 44 , 45 ]. And the incidence of other infectious diarrheal diseases has continued to rise in recent years, which is consistent with the results of most studies[ 46 , 47 ]. Most of the epidemic outbreaks are dominated by norovirus since 2013, and the key to blocking them is to reduce environmental pollution and focus on dietary safety[ 48 ]. It also shows that the incidence and case-fatality rates of influenza have increased rapidly during the last decade, with low influenza vaccine coverage being an important reason for its high prevalence[ 49 – 51 ]. High incidence of the disease also increases the risk of death in specific populations, especially in people older than 60 years[ 52 ]. Therefore, there is a need to enhance influenza surveillance in the future along with boosting influenza vaccination rates for specific populations[ 53 , 54 ]. At the same time, the emerging infectious disease COVID-19 epidemic in 2020 suggests that we need to emphasize and strengthen the effective prevention, control and close monitoring of related infectious diseases, and further promote the strength and quality of the efforts, including health education, vaccine research and development, as well as the prevention and vaccination of existing vaccines[ 52 ]. From the point of view of transmission, intestinal, respiratory, and sexual, blood and mother-to-child transmission of diseases are still the "main force", of which the epidemic of intestinal infectious diseases is particularly serious. Intestinal infectious diseases are mainly caused by improper hygiene habits such as eating, drinking, etc[ 55 ]. The prevalence of COVID-19 has a certain impact on the incidence of gastrointestinal infectious diseases, and some studies have shown that the number of rotavirus and adenovirus-positive patients and the positive detection rate in 2020 will be significantly reduced compared with that in 2019[ 56 ]. For respiratory infectious diseases, they are mainly transmitted through droplets and airborne transmission[ 57 , 58 ], and a series of preventive and control measures taken against respiratory viruses such as COVID-19 have resulted in respiratory syncytial virus, influenza virus, adenovirus and other respiratory-transmissible viral infections being at a low level[ 59 ]. Both intestinal and respiratory spread are closely related to public hygiene habits, and the COVID-19 outbreak has not only promoted tremendous changes in people's hygiene concepts and behaviors, but also significantly improved their health literacy[ 60 – 63 ]. In addition, blood-borne and sexually transmitted diseases showed a significant decline, particularly prominent in February 2020, followed by an oscillating rebound[ 36 ]. In terms of seasonal distribution, diseases showed two peaks between 2013 and 2022, in summer and winter. Among them, intestinal and respiratory infectious diseases mainly showed some seasonality, with the onset of intestinal infectious diseases concentrated in May-July, and respiratory infectious diseases in January, June-July, and December. This may be related to the fact that high temperatures and humidity in summer facilitate the multiplication and spread of pathogens, whereas in winter, cold and dry climatic conditions favor the survival and spread of viruses. In our study, there are some limitations. Firstly, the data we used were all obtained from publicly available government information, however, the information on the regional distribution, age and gender composition of each infectious disease in these data was not comprehensive, so that we were not able to further analyze the spatial distribution of the notifiable infectious diseases, the regional differences, and the high-risk groups. Secondly, based on the data from the reporting system, we may underestimate the annual incidence rates affected by the intensity of screening. This means that, for some reasons, certain infectious diseases may not be adequately screened and therefore their incidence rates may be underestimated. Then, the incidence of certain infectious diseases may also be underestimated due to self-selection ascertainment bias, that is, people with a particular infectious disease are more likely to avoid screening than people without that infection. This implies that even if someone knows they have a particular infectious disease, they may choose not to be screened, resulting in an underestimation of the incidence of that infectious disease. Furthermore, potential biases may arise due to differences in diagnostic criteria, skill levels and laboratory conditions in different sectors or institutions, which may affect the accuracy of incidence and case-fatality reporting. Conclusions This study indicates that China has made remarkable achievements in the prevention and treatment of infectious diseases. Behind these achievements are not only the aggressive engagement and scientific management of governmental departments, but also the extensive participation and joint efforts of all sectors of society. In spite of these achievements, major infectious diseases such as AIDS, tuberculosis and viral hepatitis, as well as highly prevalent infectious diseases such as hand-foot-mouth disease, influenza and infectious diarrhea diseases, are still posing a serious threat to the lives and health of the population, and the rapid spread of these diseases and the wide range of their impacts are exerting tremendous economic pressure and psychological burden on the community. More importantly, the risk of recurrence of old infectious disease outbreaks and the risk of new infectious disease outbreaks are ever-present, posing a new challenge to global public health. Therefore, we need to remain vigilant at all times, continue to strengthen the implementation of prevention and control measures, and enhance the public's health awareness and self-protection capabilities, so as to jointly safeguard the harmony and stability of society and the health and well-being of the people. Declarations Authors’ contributions HR Zhou, KY Ye, N Xiao and L Ai designed the study. HR Zhou, XL Wang, Z Zhou, YF Wang and JF Hu collected the materials. HR Zhou, XL Wang and XM Wang analyzed the data. HR Zhou and XL Wang drafted the initial manuscript. GF Li, KY Ye, N Xiao and L Ai contributed to the critical revision of the article. HR Zhou, XL Wang, KY Ye, N Xiao and L Ai reviewed and edited the content of the whole paper. All authors reviewed subsequent drafts of the manuscript and approved the final version. Funding 1. The Fifth Round of Discipline Leader Fostering Program of Shanghai Qingpu District Public Health System (XD2023-29) 2. Shanghai Center for Disease Control and Prevention Junior Core Component Talent Project (22QNGG28) Ethics declarations Ethics approval and consent to participate The information in our study was reported by the Division of Infectious Disease, Chinese Center for Disease Control and Prevention, which is routine surveillance. 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Zhou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIiWNgGAWjYBACAwYGNiAlIcfP33zgA0iEjZ04LTbGkjOOJc4Aa2EmTkta4oYDOYZgLQyEtJhLH3/24GPbYcaGA2c+Nnxs2ybPx8zA+OFjDm4tln0J6YYz2w4zMzb3bmyccea2YRszA7PkzG14HHaG4Zg0b9thoA/Obn/MU3GbEaiFjZkXrxbGNpAWHjaGnIfNPAa37YnQwswG1JImwcOQw9gMtCWRCC1sbJIzztkYSEgcMwT5JbkN6C0CfmF/JvGhTKJ+//nmh8AQu207v7354IePeLRgA4wNpKkfBaNgFIyCUYABAO6dUGklR72MAAAAAElFTkSuQmCC","orcid":"","institution":"Qingpu District Center for Disease Control and Prevention，Shanghai","correspondingAuthor":true,"prefix":"","firstName":"Hongrang","middleName":"","lastName":"Zhou","suffix":""},{"id":268002786,"identity":"0b9673d5-638e-4001-a9f7-cdb2a7c273e9","order_by":1,"name":"Xiaoling Wang","email":"","orcid":"","institution":"School of Life Sciences，Fudan University，Shanghai，China","correspondingAuthor":false,"prefix":"","firstName":"Xiaoling","middleName":"","lastName":"Wang","suffix":""},{"id":268002787,"identity":"67025ae4-215b-44b8-979c-db820ead0c81","order_by":2,"name":"Guifu Li","email":"","orcid":"","institution":"Qingpu District Center for Disease Control and Prevention, Shanghai,China","correspondingAuthor":false,"prefix":"","firstName":"Guifu","middleName":"","lastName":"Li","suffix":""},{"id":268002788,"identity":"4a73175c-b6e3-4eb1-a3e2-c1def61cb8ed","order_by":3,"name":"Zhe Zhou","email":"","orcid":"","institution":"Qingpu District Center for Disease Control and Prevention,Shanghai,China","correspondingAuthor":false,"prefix":"","firstName":"Zhe","middleName":"","lastName":"Zhou","suffix":""},{"id":268002789,"identity":"0c1a8caf-2173-4a31-b143-f583ad72e54f","order_by":4,"name":"Xiaoming Wang","email":"","orcid":"","institution":"Program in Public Health,College of Health Sciences,University of California at Irvine,Irvine,CA 92697 USA","correspondingAuthor":false,"prefix":"","firstName":"Xiaoming","middleName":"","lastName":"Wang","suffix":""},{"id":268002790,"identity":"f490c06a-18a8-4ce2-9e2c-7fa3e6a68443","order_by":5,"name":"Jingfei Hu","email":"","orcid":"","institution":"Qingpu District Center for Disease Control and Prevention,Shanghai,China","correspondingAuthor":false,"prefix":"","firstName":"Jingfei","middleName":"","lastName":"Hu","suffix":""},{"id":268002791,"identity":"e2e2d2ba-be68-4a37-8d01-387c83473be7","order_by":6,"name":"Yufeng Wang","email":"","orcid":"","institution":"Qingpu District Center for Disease Control and Prevention,Shanghai,China","correspondingAuthor":false,"prefix":"","firstName":"Yufeng","middleName":"","lastName":"Wang","suffix":""},{"id":268002792,"identity":"8c67dae2-916f-47d8-9f03-16b13d86897f","order_by":7,"name":"Muxin Chen","email":"","orcid":"","institution":"Hainan Tropical Diseases Research Center(Hainan Sub-Center,Chinese Center for Tropical Diseases Research),Haikou,China","correspondingAuthor":false,"prefix":"","firstName":"Muxin","middleName":"","lastName":"Chen","suffix":""},{"id":268002793,"identity":"37de8e54-e889-4ebf-88b7-874ed101deb1","order_by":8,"name":"Kaiyou Ye","email":"","orcid":"","institution":"Qingpu District Center for Disease Control and Prevention,Shanghai,China","correspondingAuthor":false,"prefix":"","firstName":"Kaiyou","middleName":"","lastName":"Ye","suffix":""},{"id":268002794,"identity":"d6e9dd10-dc32-468c-a77d-0aac8b255f94","order_by":9,"name":"Ning Xiao","email":"","orcid":"","institution":"Hainan Tropical Diseases Research Center(Hainan Sub-Center,Chinese Center for Tropical Diseases Research),Haikou,China","correspondingAuthor":false,"prefix":"","firstName":"Ning","middleName":"","lastName":"Xiao","suffix":""},{"id":268002795,"identity":"cc04aa81-1dd4-429f-8965-b99efa9da09f","order_by":10,"name":"Lin Ai","email":"","orcid":"","institution":"Institute of Microbiology Laboratory,Shanghai Municipal Center for Disease Control and Prevention,Shanghai 20036,China","correspondingAuthor":false,"prefix":"","firstName":"Lin","middleName":"","lastName":"Ai","suffix":""}],"badges":[],"createdAt":"2024-01-13 16:04:04","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-3860619/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3860619/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49992087,"identity":"d29b1869-783e-475c-a22a-72115c1c2bf1","added_by":"auto","created_at":"2024-01-22 18:53:27","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":667190,"visible":true,"origin":"","legend":"\u003cp\u003eIncidence and case-fatality ratios data for 45 notifiable infectious diseases of China from 2013 to 2022.(A) Incidence of 45 notifiable infectious diseases. (B) Case-fatality ratios of 45 notifiable infectious diseases. (C) Number of cases and incidence rate per year between 2013 and 2022. (D) Number of deaths and case-fatality ratios per year between 2013 and 2022. *Total numbers for 10 years. #Average for 10 years. §Infectious diarrhea excludes cholera, dysentery, typhoid fever and paratyphoid fever. HFMD=hand, foot, and mouth disease. AIDS=Acquired immune deficiency syndrome. AHC=Acute haemorrhagic conjunctivitis.TF\u0026amp;PF=Typhoid fever and paratyphoid fever. EHF=Epidemic hemorrhagic fever. H7N9=Human infection with H7N9 virus. H5N1=Human infection with H5N1 virus. SARS=severe acute respiratory syndrome.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3860619/v1/77065e702088d2935a8f9262.jpeg"},{"id":49992086,"identity":"4454b986-6856-4ac2-9680-0d50137663d9","added_by":"auto","created_at":"2024-01-22 18:53:27","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":272313,"visible":true,"origin":"","legend":"\u003cp\u003eThe proportion of cases and deaths of 45 infectious diseases stratified by transmission routes of China from 2013 to 2022.(A) The proportion of cases of 45 notifiable infectious diseases of China from 2013 to 2022.(B) The proportion of deaths of 45 notifiable infectious diseases of China from 2013 to 2022. According to their transmission route, 45 infectious diseases were classified as follows: respiratory (12) (SARS-CoV, Measles, Tuberculosis, Meningococcal meningitis, Pertussis, Diphtheria, Scarlet fever, Leprosy, Influenza (H1N1 influenza A), Mumps, Rubella, and COVID-19); intestinal (9) (Cholera, Hepatitis A, Hepatitis E, Other hepatitis, Poliomyelitis, Dysentery, TF\u0026amp;PF, Infectious diarrhea§, and HFMD); zoonotic infectious diseases(8) (Plague, EHF, Rabies, Brucellosis, Leptospirosis, Echinococcosis, Human infection with H5N1 and H7N9 virus); vector-borne infectious diseases (6) (Japanese encephalitis, Dengue, Malaria, Typhus, Kala azar and Filariasis); sexual, blood-borne, and mother-to-child-borne infectious diseases (6) (AIDS, Hepatitis B, Hepatitis C, Hepatitis D, Gonorrhea and Syphilis); other transmission (4) (Anthrax, Neonatal tetanus, Schistosomiasis and AHC).\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3860619/v1/66c7c61f832d5c61b0f1e3b4.jpeg"},{"id":49992088,"identity":"aaf649a0-8e1f-4b10-abb7-5d7d8fd951d9","added_by":"auto","created_at":"2024-01-22 18:53:27","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":513505,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of incidence and case-fatality ratios of 45 notifiable infectious diseases in China by month from 2013 to 2022. (A) Monthly incidence and case-fatality ratios data for 45 notifiable infectious diseases of China from 2013 to 2022.(B) Seasonal index of months of incidence of 45 notifiable infectious diseases in China from 2013 to 2022.(C) Seasonal index of months of case-fatality ratios of 45 notifiable infectious diseases in China from 2013 to 2022.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3860619/v1/091d4101f0e208e80c7f9f3d.jpeg"},{"id":50066639,"identity":"3b3488fb-203a-4952-8a2c-bd218aecb17b","added_by":"auto","created_at":"2024-01-24 00:51:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1076675,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3860619/v1/fd241a70-d21f-4856-938c-b9264e21c283.pdf"},{"id":49992089,"identity":"efc4eceb-a8a5-4142-af07-dff4a1ab9c88","added_by":"auto","created_at":"2024-01-22 18:53:27","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":3170931,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-3860619/v1/f4a3371deb5cfac83f926294.docx"}],"financialInterests":"","formattedTitle":"The epidemiological trends of 45 national notifiable infectious diseases in China: An analysis of national surveillance data from 2013 to 2022","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWith the changes in ecological environment and human behavior, the emergence of new infectious diseases and the resurgence of established infectious diseases have led to new threats to human beings[\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Since the 21st century, with the improvement of sanitary conditions and nutritional status of the populations, the development of diagnostic and therapeutic techniques, vaccines and drugs have been adopted[\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Most infectious diseases have been effectively controlled and some had even been eliminated[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Nonetheless, with the economic growth and urbanization acceleration,, the prevention and control of infectious diseases did not further strengthen correspondingly, leading to the resurgence and epidemic of traditional infectious diseases like tuberculosis. Simultaneously, novel infectious diseases have emerged due to increased international exchanges and ecological environment changes, such as SARS[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], poliomyelitis[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], pandemic H1N1 influenza[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], avian influenza A H5N1, avian influenza A H7N9[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] and COVID-19[\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. These emerging infectious diseases not only impose a significant economic burden on China but also pose a grave threat to public life safety[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. To effectively prevent and control infectious diseases, the China has implemented a series of measures, including shifting from non-synergistic to cooperative, multi-sectoral, and One Health integrated prevention and control strategies[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Through interdisciplinary collaboration and combined prevention and treatment, our country has achieved remarkable achievements in the prevention and treatment of infectious diseases.\u003c/p\u003e \u003cp\u003eInfectious disease surveillance is a crucial public health monitoring assignment which not only requires a long-term continuously, but also requires an in-depth comprehension of the epidemiological patterns of infectious diseases and assessment of the effects of the interventions. China has established a national standardized reporting system for notifiable infectious diseases in the 1950s[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] and an Internet-based case reporting system in 2003[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], which has provided strong support for the prevention and control of infectious diseases.\u003c/p\u003e \u003cp\u003eIn this investigation, we extracted epidemic data reported by the National Infectious Disease Surveillance System (NIDSS) in mainland China (excluding Hong Kong, Macao, and Taiwan) from 2013 to 2022, including the relevant data during the COVID-19 epidemic. Through analyzing the epidemiological characteristics and trends of infectious diseases in past ten years across the country, we try to further explore and understand the epidemiological patterns of infectious diseases, evaluate the situation of epidemics, and provide references and bases for the formulation of strategies and measures for the prevention and control of infectious diseases.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData sources\u003c/h2\u003e \u003cp\u003eThe data come from the monthly analysis report of the NIDSS from 2013 to 2022, which was reported by the Division of Infectious Disease, Chinese Center for Disease Control and Prevention. The data includes the numbers of cases and deaths per month. The annual population data for the years from 2013 to 2022 were collected from the data published on the website of the Chinese National Bureau of Statistics.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eProcedures\u003c/h2\u003e \u003cp\u003eChina established a system of routine reporting on notifiable infectious diseases in the 1950s. The system currently covers data from 31 provinces in mainland China, with a coverage of approximately 1.4\u0026nbsp;billion people. This system has been updated web-based since 2003 and operated through administrative grading responsibility and territorial management. The number of notifiable infectious diseases included in the reporting system is increasing from 18 before 1978 to 40 after 2020[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChanges to the list of notifiable diseases in China, 1955\u0026ndash;2022\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNo. of diseases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eNo. of the different classes of the diseases (including newly added )\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCancel-reporting\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (Plague, cholera, smallpox)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (Epidemic encephalitis B, diphtheria, scrubtyphus, relapsing fever, dysentery, typhoid fever, scarlet fever, epidemic cerebrospinal meningitis, measles, poliomyelitis, pertussis, anthrax, undulant fever, forest encephalitis and rabies)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1978\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (Influenza, viral hepatitis\u003csup\u003e\u003cb\u003e#\u003c/b\u003e\u003c/sup\u003e, tsutsugamushi disease, epidemic haemorrhagic fever, leptospirosis, brucellosis, malaria)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 ( HIV/AIDS, gonorrhea, syphilis, kala-azar, dengue fever)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11 (Epidemic encephalitis B, tuberculosis, schistosomiasis, filariasis, echinococcosis, lepra, epidemic parotitis, rubella, neonatal tetanus, acute hemorrhagic\u003c/p\u003e \u003cp\u003econjunctivitis, other infectious diarrhea*)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (Smallpox, relapsing fever, forest encephalitis, Tsutsugamushi disease, undulant fever)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25 (Tuberculosis, schistosomiasis, neonatal tetanus, SARS and highly pathogenic avian influenza A H5N1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 (Scrubtyphus and kala-azar)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11 (Hand, foot and mouth disease)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (Influenza A H1N1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (H7N9 avian influenza)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eInfluenza A H1N1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (COVID-19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e#Viral hepatitis consists of six types: hepatitis A, hepatitis B, hepatitis C, hepatitis D, hepatitis E, and unclassified hepatitis. And hepatitis D has been included in the Communicable Disease Report since 2016. *Other infectious diarrhea refers to diarrhea other than that caused by cholera, dysentery or typhoid fever.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAccording to the \u0026ldquo;Law of the People's Republic of China on Prevention and Control of Infectious Diseases\u0026rdquo;, the notifiable infectious diseases are classified into classes A, B and C. Among them, there are 2 in type A, 27 in type B, and 11 in type C[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] (Supplementary S1). And Influenza A H1N1 was only reported in 2009\u0026ndash;2013, as H1N1 was included in the monitoring of influenza viruses in 2014, this study combined the H1N1 influenza data with those of other influenza viruses for statistical analysis[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In addition, viral hepatitis was subdivided into hepatitis A, B, C, D, E and unclassified. In this study, we analyzed the data strictly according to the classification criteria of notifiable infectious diseases.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eYearly incidence (per 100000) was the number of reported cases per year divided by the mid-year population size. The fatality rate (per 1000) was the number of reported deaths divided by the number of reported cases over the same period[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In addition, radar charts based on the percentage of patients per month to characterize the distribution of the diseases throughout the year were applied.\u003c/p\u003e \u003cp\u003eMicrosoft Excel 2010 (Microsoft, Redmond, WA, USA) was utilized for data extraction, sorting and cleaning. The joinpoint regression models[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] were used to examine incidence and case-fatality rate trends from 2013 to 2022 and to identify changes in trends at every stage. The software Joinpoint Regression Program Version 5.0.2 (Statistical Research and Applications Branch, National Cancer Institute) was employed to build the joinpoint regression models, calculate annual percentage changes (APC) and average annual percentage changes (AAPC) to express trends. If the point of joinpoint regression models is zero, then AAPC\u0026thinsp;=\u0026thinsp;APC, and when APC\u0026thinsp;\u0026gt;\u0026thinsp;0, it indicates an upward trend; when APC\u0026thinsp;\u0026lt;\u0026thinsp;0, it indicates a downward trend, when APC\u0026thinsp;=\u0026thinsp;0, it indicates a steady state[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. We also calculated 95% confidence intervals for APCs and AAPCs and tested hypotheses using Z test with P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 as the significance level.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eOverall incidence and case-fatality ratios\u003c/h2\u003e \u003cp\u003eThis study covered 45 infectious diseases during the period from 2013 to 2022. In this 10-year period, the total number of reported cases of infectious diseases amounted to 76,874,318, with an average annual incidence rate of 551.26/100,000. HFMD, hepatitis B, infectious diarrhea, tuberculosis, and influenza were the five diseases with the highest average annual incidence rates for this period, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA (Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Among the 76,874,318 cases of infectious disease, 207,216 deaths were recorded, representing an average yearly case-fatality ratio of 2.70 deaths per 1000 cases per year. AIDS, tuberculosis, infectious diarrhea, COVID-19, and hepatitis C account for the highest mortality rates,, while rabies, H5N1 influenza, plague, H7N9 influenza, and AIDS have the highest case-fatality ratios, as depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB (Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). From 2013 to 2019, the annual incidence rate of the total disease continued to rise by a staggering 48.83%, and this trend was confirmed by the number of cases. In the following period from 2020 to 2022, although the annual incidence rate of the overall disease has declined, it still shows an increasing trend in this period, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC (Supplementary Table S2). Meanwhile, the rate of deaths from diseases in general was also increasing during the period from 2013 to 2022, which is consistent with the trend in the number of disease deaths. It is interesting to realize that the number of disease deaths showed no significant fluctuation or even a slight decrease during the epidemic of COVID-19, but the rate of disease deaths showed a relatively large increase, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD (Supplementary Table S2).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEpidemic trend of 45 infectious diseases stratified by A, B and C\u003c/h2\u003e \u003cp\u003eAccording to official statistical data, from 2013 to 2022, the incidence of notifiable infectious diseases in mainland China was dominated by type C infectious diseases, which accounted for 54.50% of the total number of cases, and the incidence of type B infectious diseases accounted for 45.498%, while the incidence of type A infectious diseases was much lower than 0.01% (Supplementary Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, Tables S3 and S4). The total incidence of the three types of infectious diseases decreased during this period, with an AAPC of -0.14% (95% CI: -3.75\u0026ndash;3.51%). However, the case-fatality ratio of the diseases showed an increasing trend, with an AAPC of 5.41% (95% CI: 2.29\u0026ndash;8.61%). Among them, the incidence rates of both type A and B infectious diseases showed a decreasing trend, with AAPCs of -8.69% (95% CI: -22.78 to 7.63%) and \u0026minus;\u0026thinsp;1.67% (95% CI༚-2.51 to -0.82%), respectively. But the case-fatality rates of both were on the rise, with AAPCs of 5.22% (95% CI༚-10.74 to 22.69%) and 7.33% (95% CI༚-4.82 to 9.85%), respectively. In contradistinction to infectious diseases of type A and B, the incidence of infectious diseases of type C showed an increasing trend, with an AAPC of 1.14% (95% CI: -5.29 to 7.84%). The case-fatality rate for type C infectious diseases, however, showed a decreasing trend, with an AAPC of -28.44% (95% CI: -41.69 to -8.04%).\u003c/p\u003e \u003cp\u003eAdditionally, the data of three years before and after the COVID-19 outbreak were carefully analysed in this study for comparison (Supplementary Table S5). According to the analysis, the total average annual incidence rate during the outbreak period (2020\u0026ndash;2022) decreased compared with the pre-outbreak period (2017\u0026ndash;2019), with a decrease of 23.32%. The incidence rates of infectious diseases in type A, B, and C have decreased, with the most significant decrease in type C infectious diseases at 31.27%. In terms of case-fatality rate, however, the performance was the opposite of the incidence rate, with an increase of 38.77%. In particular, the case-fatality rate of infectious diseases of type A and B increased by 137.04% and 21.53%, while the case-fatality rate of infectious diseases of type C decreased by 55.65%, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnnual percentage change in incidence and case-fatality ratios of 45 infectious diseases stratified by A, B and C, from 2013 to 2022\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTypes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eYearly incidence rate (per 100 000)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eCase-fatality ratios (per 1000)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDuration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAPC%\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAAPC %\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2017-2019VS 2020\u0026ndash;2022(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDuration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAPC%\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAAPC %\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2017-2019VS 2020\u0026ndash;2022(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2013\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-8.69\u003c/p\u003e \u003cp\u003e(-22.78 to 7.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-8.69\u003c/p\u003e \u003cp\u003e(-22.78 to 7.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-16.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2013\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.22\u003c/p\u003e \u003cp\u003e(-10.74 to 22.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.22\u003c/p\u003e \u003cp\u003e(-10.74 to 22.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e137.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2013\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.67*\u003c/p\u003e \u003cp\u003e(-2.51 to -0.82)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.67*\u003c/p\u003e \u003cp\u003e(-2.51 to -0.82)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-11.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2013\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.33*\u003c/p\u003e \u003cp\u003e(4.82 to 9.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.33*\u003c/p\u003e \u003cp\u003e(4.82 to 9.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e21.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2013\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003cp\u003e(-5.29 to 7.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003cp\u003e(-5.29 to 7.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-31.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2013\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-14.68\u003c/p\u003e \u003cp\u003e(-49.59 to 152.27)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-28.44*\u003c/p\u003e \u003cp\u003e(-41.69 to -8.04)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-55.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2020\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-61.34*\u003c/p\u003e \u003cp\u003e(-86.59 to -4.59)\u003c/p\u003e\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2013\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.14\u003c/p\u003e \u003cp\u003e(-3.75 to 3.51)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.14\u003c/p\u003e \u003cp\u003e(-3.75 to 3.51)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-23.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2013\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.41*\u003c/p\u003e \u003cp\u003e(2.29 to 8.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.41*\u003c/p\u003e \u003cp\u003e(2.29 to 8.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e38.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eAPC, annual percent change; AAPC, average annual percent change. * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eEpidemic trend of 45 infectious diseases in different transmission routes\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and B (Supplementary Table S6 and S7), we can observe that during the period from 2013 to 2022, notifiable infectious diseases in mainland China are predominantly characterized by intestinal infectious diseases, accounting for 40.64% of the total number of cases. Respiratory infectious diseases and sexual, blood and mother-to-child borne infectious diseases also occupy a considerable proportion, accounting for 30.82% and 26.90%. However, zoonotic, vector borne and other (contact) infections represented less than 1.00% of the total. In terms of deaths from related diseases, sexual, blood and mother-to-child borne of infectious diseases were the main contributors, accounting for 83.19% of the total number of deaths. Respiratory and zoonotic infectious diseases also accounted for a certain proportion, accounting for 12.49% and 3.08%. Similarly, intestinal, vector borne and other (contact) infections accounted for less than 1.00% of deaths.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTrends in the incidence and case-fatality rates of the various infectious diseases showed varying trends over the past decade. The incidence rates of the intestinal, sexual, blood and mother-to-child borne, and other (contact) infections diseases showed an increasing trend, with AAPCs of 6.27% (95% CI: -1.47 to 14.44), 1.26% (95% CI: -2.47 to 4.21), and 0.87% (95% CI: -0.64 to 2.53). In terms of case-fatality rates, there was an increasing trend for intestinal and other (contact) infections diseases, while there was a decreasing trend for sexual, blood and mother-to-child borne, with AAPCs of 0.60% (95% CI: -8.35 to 10.42) and 4.29% (95% CI: 3.44 to 5.01), and \u0026minus;\u0026thinsp;21.32% (95% CI: -25.84 to \u0026minus;\u0026thinsp;16.76). Respiratory, zoonotic and vector borne types of infectious diseases showed a decreasing trend, with AAPCs of -6.81% (95% CI: -11.14 to -2.07), -19.65% (95% CI: -33.41 to -3.52), and \u0026minus;\u0026thinsp;5.89% (95% CI: -12.32 to -0.61). Regarding case-fatality rates, all of them also showed a decreasing trend, with AAPCs of -22.61% (95% CI: -30.24 to -14.26), -1.58% (95% CI: -19.89 to 21.02) and \u0026minus;\u0026thinsp;21.72% (95% CI: -25.81 to -15.14), as shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (Supplementary Tables S8).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnnual percentage change in incidence and case-fatality ratios of 45 infectious diseases stratified by different transmission routes, from 2013 to 2022.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTypes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eYearly incidence rate (per 100 000)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eCase-fatality ratios (per 1000)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDuration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAPC%\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAAPC %\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2017-2019VS 2020\u0026ndash;2022(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDuration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAPC%\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAAPC %\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2017-2019VS 2020\u0026ndash;2022(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntestinal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2013\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.27\u003c/p\u003e \u003cp\u003e(-1.47 to 14.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.27\u003c/p\u003e \u003cp\u003e(-1.47 to 14.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-39.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2013\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003cp\u003e(-8.35 to 10.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003cp\u003e(-8.35 to 10.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-33.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRespiratory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2013\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.24\u003c/p\u003e \u003cp\u003e(-5.53 to 27.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-6.81*\u003c/p\u003e \u003cp\u003e(-11.14 to -2.07)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-17.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2013\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-22.61*\u003c/p\u003e \u003cp\u003e(-30.24 to -14.26)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-22.61*\u003c/p\u003e \u003cp\u003e(-30.24 to -14.26)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e87.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-15.97*\u003c/p\u003e \u003cp\u003e(-34.34 to -7.98)\u003c/p\u003e\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSexual, blood and mother-to-\u003c/p\u003e \u003cp\u003echild borne\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2013\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.93\u003c/p\u003e \u003cp\u003e(-17.59 to 1.49)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003cp\u003e(-2.47 to 4.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-4.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2013\u0026ndash;2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-7.85\u003c/p\u003e \u003cp\u003e(-17.44 to 18.07)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-21.32*\u003c/p\u003e \u003cp\u003e(-25.84 to -16.76)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e9.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2019\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003cp\u003e(-0.44 to 33.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2017\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-30.66*\u003c/p\u003e \u003cp\u003e( -43.93 to -25.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZoonotic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2013\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-19.65*\u003c/p\u003e \u003cp\u003e(-33.41 to -3.52)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-19.65*\u003c/p\u003e \u003cp\u003e(-33.41 to -3.52)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2013\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1.58\u003c/p\u003e \u003cp\u003e(-19.89 to 21.02)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-1.58\u003c/p\u003e \u003cp\u003e(-19.89 to 21.02)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-70.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eOther (contact)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2013\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2.59*\u003c/p\u003e \u003cp\u003e(0.08 to 10.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003cp\u003e(-0.64 to 2.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e-31.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2013\u0026ndash;2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.82\u003c/p\u003e \u003cp\u003e(-0.18 to 6.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e4.29*\u003c/p\u003e \u003cp\u003e(3.44 to 5.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e-33.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2016\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.18*\u003c/p\u003e \u003cp\u003e(6.42 to 11.47)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2019\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2.49\u003c/p\u003e \u003cp\u003e(-10.37 to 1.90)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2019\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003cp\u003e(-4.06 to 2.50)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVector borne\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2013\u0026ndash;2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.02\u003c/p\u003e \u003cp\u003e(-10.05 to 57.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-5.89*\u003c/p\u003e \u003cp\u003e(-12.32 to -0.61)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-80.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2013\u0026ndash;2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-57.01*\u003c/p\u003e \u003cp\u003e(-66.69 to -32.27)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-21.72*\u003c/p\u003e \u003cp\u003e(-25.81 to -15.14)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-38.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2015\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-12.00*\u003c/p\u003e \u003cp\u003e(-32.63 to -3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2015\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-7.10\u003c/p\u003e \u003cp\u003e(-13.31 to 10.16)\u003c/p\u003e\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2013\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.14\u003c/p\u003e \u003cp\u003e(-3.75 to 3.51)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.14\u003c/p\u003e \u003cp\u003e(-3.75 to 3.51)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-23.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2013\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.41*\u003c/p\u003e \u003cp\u003e(2.29 to 8.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.41*\u003c/p\u003e \u003cp\u003e(2.29 to 8.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e38.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eAPC, annual percent change; AAPC, average annual percent change. * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn accordance with the results of the study, the average annual incidence rates of infectious diseases spread by all routes excluding zoonotic infectious diseases decreased during the epidemic, compared with the average of the three years preceding the COVID-19 epidemic (Supplementary Tables S8). Vector borne infectious diseases showed the greatest decrease, with a decrease of 80.56%, followed by intestinal infectious diseases, with a decrease of 39.57%. As for the case-fatality rate, the average annual case-fatality rates of infectious diseases through intestinal, zoonotic, vector borne and other (contact) infectious diseases during the epidemic were lower than those before the epidemic. Of these, infectious diseases of zoonoti showed the highest decrease, by 70.69%, followed by vector borne with a decrease of 38.55%. Respiratory and sexual, blood and mother-to-child borne diseases were both higher during the COVID-19 epidemic than before the epidemic, with rises of 87.18% and 9.27%, respectively.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSeasonal distribution of infectious diseases.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAs Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA shows (Supplementary Table S9), the total monthly incidence trend of notifiable infectious diseases in mainland China shows a \"W\" distribution from 2013 to 2022, including the monthly incidence trend in the three years before and during the COVID-19 epidemic. It should be emphasized that although the monthly incidence rates in the three years before the COVID-19 epidemic were higher than those in the 2013\u0026ndash;2022 period, the monthly incidence rates during the COVID-19 epidemic were lower than those in the 2013\u0026ndash;2022 period (except for January). Compared with the 3 years prior to the COVID-19 epidemic and the 2013\u0026ndash;2022 period, the monthly case fatality rates during the epidemic were higher than the former two except for January and November. Based on the calculation of the average seasonal index for each month of notifiable infectious disease incidence in mainland China from 2013 to 2022, the results showed that the seasonal indexes for January, May through July, and December were 1.08, 1.15, 1.31, 1.23, and 1.07, respectively, which indicated that the number of cases in these months was higher than the average for the whole year, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB. The seasonal index for case-fatalities was 1.03, 1.07, 1.15 and 1.30 for the months of August-September and November-December respectively, indicating that the number of case-fatalities in these months was higher than the average, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMeanwhile, this study utilized radar charts to provide insights into the monthly incidence and monthly case-fatality trends of each infectious disease. As for monthly incidence rates, 9 infectious diseases showed significant seasonal characteristics, 19 infectious diseases showed aggregated seasonal characteristics, and 15 infectious diseases showed no significant seasonal characteristics. With respect to monthly case-fatality rates, 11 infectious diseases showed significant seasonal characteristics, 22 infectious diseases exhibited aggregated seasonal characteristics, while no significant seasonal characteristics were observed for 6 infectious diseases (Supplementary Figure S2).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eTrends in incidence and case-fatality ratios for 45 infectious diseases\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows that from 2013 to 2022, the incidence of 7 out of 45 infectious diseases, including HIV, pertussis, diphtheria, syphilis, brucellosis, influenza, and scarlet fever, showed a significant upward trend. Specifically, pertussis and influenza had fastest increasing rates, with AAPCs of 25.90% (95% CI: 12.13 to 54.64) and 43.83% (95% CI: 24.48 to 168.87). Simultaneously, the incidence rates of 22 infectious diseases showed a significant downward trend, with the fastest decreases in schistosomiasis, mumps, rubella and neonatal tetanus, with AAPCs of -44.53% (95% CI: -77.12 to -32.19), -40.72% (95% CI: -59.40 to -36.92), -34.11% (95% CI: -63.66 to -23.81) and \u0026minus;\u0026thinsp;31.81% (95% CI: -36.28 to -29.62). And 4 of the 45 infectious diseases showed a significant upward trend in case-fatality rates during this period, including HIV, tuberculosis, scarlet fever, and rubella. Of particular note, rubella and scarlet fever showed a fastest increases, with AAPCs of 237.87% (95% CI: 223.08 to 3030.81) and 37.41% (95% CI: 16.00 to 102.81). In addition, 10 infectious diseases showed significant decreases in case-fatality rates. Among them, typhus, cholera, and schistosomiasis showed a fastest rate of decline, with AAPCs of -63.33% (95% CI: -88.13 to -63.63), -44.50% (95% CI: -58.39 to -37.06) and \u0026minus;\u0026thinsp;37.23% (95% CI: -78.49 to -27.01).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnnual percentage change in incidence of 45 infectious diseases, from 2013 to 2022\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eItems\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYearly incidence\u0026dagger;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCase-fatality ratios\u0026dagger;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eComparison of the incidence and fatality ratios in the three years before and after the COVID-19 outbreak (2017\u0026ndash;2019 vs 2020\u0026ndash;2022)༈%༉\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAAPC (95% CI) /%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAAPC (95% CI) /%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYearly incidence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCase-fatality ratios\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlague\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-13.39*\u003c/p\u003e \u003cp\u003e( -44.72 to -4.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-8.42\u003c/p\u003e \u003cp\u003e(-20.76 to 5.39)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCholera\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-8.13\u003c/p\u003e \u003cp\u003e(-23.62 to 5.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-44.50*\u003c/p\u003e \u003cp\u003e(-58.39 to -37.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-19.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSARS-CoV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAIDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.93*\u003c/p\u003e \u003cp\u003e(1.00 to 2.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.58*\u003c/p\u003e \u003cp\u003e(2.99 to 4.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-10.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHepatitis A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-9.46*\u003c/p\u003e \u003cp\u003e(-12.65 to -6.87)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.17\u003c/p\u003e \u003cp\u003e(-11.11 to 2.41)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-31.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-21.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHepatitis B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003cp\u003e(-0.50 to 2.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-5.46*\u003c/p\u003e \u003cp\u003e(-7.44 to -3.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-3.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHepatitis C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.19\u003c/p\u003e \u003cp\u003e(-1.17 to 0.81)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.58\u003c/p\u003e \u003cp\u003e(-0.66 to 10.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-8.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHepatitis D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-13.35*\u003c/p\u003e \u003cp\u003e(-18.36 to -8.55)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-44.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHepatitis E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.78\u003c/p\u003e \u003cp\u003e(-4.69 to 1.18)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2.57\u003c/p\u003e \u003cp\u003e(-9.13 to 3.77)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-17.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-22.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther hepatitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-17.79*\u003c/p\u003e \u003cp\u003e(-19.92 to -16.64)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.68\u003c/p\u003e \u003cp\u003e(-11.87 to 0.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-51.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e102.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoliomyelitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH5N1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-5.00\u003c/p\u003e \u003cp\u003e(-15.46 to 2.94)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.93\u003c/p\u003e \u003cp\u003e(-18.94 to 14.68)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeasles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-40.72*\u003c/p\u003e \u003cp\u003e(-59.40 to -36.92)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-5.71\u003c/p\u003e \u003cp\u003e(-25.93 to 13.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-78.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-100.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEHF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-5.77*\u003c/p\u003e \u003cp\u003e(-10.15 to -1.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2.60\u003c/p\u003e \u003cp\u003e(-11.49 to 5.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-31.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRabies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-22.52*\u003c/p\u003e \u003cp\u003e(-24.72 to -21.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.22\u003c/p\u003e \u003cp\u003e(-2.64 to 1.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-59.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-8.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEpidemic encephalitis B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-29.34*\u003c/p\u003e \u003cp\u003e(-42.77 to -24.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-10.81*\u003c/p\u003e \u003cp\u003e(-29.69 to -3.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-80.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-62.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDengue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-17.27\u003c/p\u003e \u003cp\u003e(-43.27 to 2.98)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-6.30\u003c/p\u003e \u003cp\u003e(-11.73 to 8.07)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-95.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-100.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnthrax\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.05\u003c/p\u003e \u003cp\u003e(-2.20 to 8.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-4.26\u003c/p\u003e \u003cp\u003e(-19.10 to 12.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-54.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDysentery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-16.75*\u003c/p\u003e \u003cp\u003e(-18.59 to -15.72)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.84\u003c/p\u003e \u003cp\u003e(-22.39 to 13.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-49.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e120.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTuberculosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-6.55*\u003c/p\u003e \u003cp\u003e(-7.50 to -5.75)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.33*\u003c/p\u003e \u003cp\u003e(7.00 to 20.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-26.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTF\u0026amp;PF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-9.45*\u003c/p\u003e \u003cp\u003e(-12.51 to -7.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.62\u003c/p\u003e \u003cp\u003e(-10.81 to 32.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-36.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeningococcal meningitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-12.53*\u003c/p\u003e \u003cp\u003e(-17.56 to -8.61)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.35\u003c/p\u003e \u003cp\u003e(-11.11 to 2.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-49.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-27.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePertussis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.90*\u003c/p\u003e \u003cp\u003e(12.13 to 54.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-23.36\u003c/p\u003e \u003cp\u003e(-43.34 to 1.98)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-15.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiphtheria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.30*\u003c/p\u003e \u003cp\u003e(0.03 to 46.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e297.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeonatal tetanus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-31.81*\u003c/p\u003e \u003cp\u003e(-36.28 to -29.62)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003cp\u003e(-19.41 to 15.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-69.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-18.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScarlet fever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-11.38*\u003c/p\u003e \u003cp\u003e(-21.39 to -3.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.41*\u003c/p\u003e \u003cp\u003e(16.00 to 102.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-71.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrucellosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.78*\u003c/p\u003e \u003cp\u003e(1.35 to 9.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.88\u003c/p\u003e \u003cp\u003e(-8.06 to 19.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-17.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGonorrhea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003cp\u003e(-3.43 to 6.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.34\u003c/p\u003e \u003cp\u003e(-5.10 to 42.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-15.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e254.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSyphilis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.65*\u003c/p\u003e \u003cp\u003e(0.28 to 2.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-5.04\u003c/p\u003e \u003cp\u003e(-11.50 to 1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-4.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeptospirosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-5.51\u003c/p\u003e \u003cp\u003e(-13.97 to 2.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-11.71*\u003c/p\u003e \u003cp\u003e(-24.05 to -4.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e151.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSchistosomiasis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-44.53*\u003c/p\u003e \u003cp\u003e(-77.12 to -32.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-37.23*\u003c/p\u003e \u003cp\u003e(-78.49 to -27.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-96.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMalaria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-18.31*\u003c/p\u003e \u003cp\u003e(-24.96 to -14.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.12\u003c/p\u003e \u003cp\u003e(-12.66 to 7.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-65.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH7N9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.00\u003c/p\u003e \u003cp\u003e(-16.56 to 132.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003cp\u003e(-12.39 to 16.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOVID-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfluenza\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.83*\u003c/p\u003e \u003cp\u003e(24.48 to 168.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-34.77*\u003c/p\u003e \u003cp\u003e(-61.63 to -3.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-8.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-63.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMumps\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-13.74*\u003c/p\u003e \u003cp\u003e(-19.83 to -9.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.14\u003c/p\u003e \u003cp\u003e(-11.41 to 25.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-56.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e588.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRubella\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-34.11*\u003c/p\u003e \u003cp\u003e(-63.66 to -23.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e237.87*\u003c/p\u003e \u003cp\u003e(223.08 to 3030.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-86.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e650.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAHC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-4.61*\u003c/p\u003e \u003cp\u003e(-9.20 to -0.26)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-11.36\u003c/p\u003e \u003cp\u003e(-75.45 to 25.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-27.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e175.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeprosy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-11.28*\u003c/p\u003e \u003cp\u003e(-13.29 to -9.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.53*\u003c/p\u003e \u003cp\u003e(-7.10 to -0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-32.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTyphus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-4.76*\u003c/p\u003e \u003cp\u003e(-6.02 to -3.57)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-63.33*\u003c/p\u003e \u003cp\u003e(-88.13 to -63.63)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKala azar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.67*\u003c/p\u003e \u003cp\u003e(1.81 to 8.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2.61\u003c/p\u003e \u003cp\u003e(-6.69 to 2.90)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEchinococcosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3.33\u003c/p\u003e \u003cp\u003e(-6.99 to 0.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.20\u003c/p\u003e \u003cp\u003e(-10.68 to 9.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-41.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFilariasis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.66\u003c/p\u003e \u003cp\u003e(-3.91 to 2.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfectious diarrhea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.46\u003c/p\u003e \u003cp\u003e(-3.22 to 6.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-14.70*\u003c/p\u003e \u003cp\u003e(-21.59 to -9.15)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-14.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-62.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHFMD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-11.19*\u003c/p\u003e \u003cp\u003e(-21.75 to -3.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-32.30*\u003c/p\u003e \u003cp\u003e(-50.38 to -23.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-55.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-74.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u0026dagger;When the number of cases or deaths data contained zero, we substitute 1\u0026permil; for zero to calculate the incidence and case-fatality rates. APC, annual percent change; AAPC, average annual percent change. * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWhen comparing the average annual incidence rates of infectious diseases before and during the COVID-19 epidemic, we found that the incidence rates of 6 infectious diseases increased during the epidemic compared with the pre-epidemic period, among which diphtheria, brucellosis, and leptospirosis showed the most significant increases, reaching 297.27%, 51.14%, and 48.04%, respectively. The incidence rates of 34 infectious diseases declined, with H7N9, schistosomiasis, dengue fever, and rubella showing the most significant decreases of 100%, 96.86%, 95.84%, and 86.76%, respectively. In terms of case-fatality rates, we found an increase in 18 diseases, with rubella, mumps, gonorrhea and AHC showing the most significant increases, reaching 650.30%, 588.96%, 254.08% and 175.19%, respectively. There were 14 diseases that showed decreases, with measles, dengue fever, HFMD and influenza showing the most significant decreases, dropping 100%, 100%, 74.20% and 63.03%, respectively.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eAccording to research findings over the years[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], infectious diseases have been closely associated with the development of society in the 21st century, and their incidence and deaths have continued to increase, posing a serious threat to people's health. After the 2003 SARS outbreak, the State Council of the People's Republic of China proposed the 2003 Emergency Regulations for Public Health Emergencies[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Subsequently, the Law of the People's Republic of China on prevention and control of infectious diseases was revised in 2004 and 2013, respectively[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. With a variety of strategies to prevent the spread of infectious diseases implemented[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], including improved safety of blood collection, large-scale vector control, and enhanced screening for early monitoring and warning, etc, there were huge achievements in the prevention and control of infectious diseases including the elimination of filariasis in 2006, neonatal tetanus in 2012, and malaria in 2021, etc[\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. However, the outbreaks and epidemics of emerging infectious diseases, such as COVID-19, have still posed new challenges to infectious disease prevention and control and in public health.\u003c/p\u003e \u003cp\u003eIn this study, the incidence of reportable diseases and the case-fatality rate show a gradual upward trend during the period from 2013 to 2019, especially the case-fatality rate. The trend is mainly attributed to the following reasons. First, with the increase in people's awareness of health, there is also an increase in attention to all types of diseases. This means that people pay more attention to the prevention, diagnosis and treatment of diseases, which promotes the rise of disease incidence. Secondly, the improvement in the level of diagnosis of infections has also contributed to the increase in incidence[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In addition, the threat of infection continues to increase with rising antimicrobial resistance, increased population mobility, changing human behavior and the emergence and spread of new infectious diseases[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. During the COVID-19 epidemic (2020 to 2022), most infectious disease incidence levels showed a greater decline, which may be related to the effectiveness of non-pharmacological interventions[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], such as since the outbreak of COVID-19, countries around the world have taken measures to control the development of the epidemic, including the wearing of face-masks, washing hands frequently, and isolation and control. These measures have played a role in preventing and controlling the spread of other pathogens, especially respiratory infections, while curbing the spread of the COVID-19 epidemic[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. It is also taken into account that the surveillance of other infectious diseases declined after the COVID-19 outbreak, which may have led to a decrease in the number of reported cases of other infectious diseases[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. In most infectious diseases, however, there was an increasing trend in case-fatality rates during this period, although the number of deaths from the corresponding diseases declined, and the main reason for this trend was mainly due to a decrease in the number of incidence cases. Of course, there are also a few diseases in which the number of deaths has risen, such as syphilis. This may be related to the fact that some patients were unable to receive timely medical care due to shyness, and the possibility cannot be ruled out that the treatment and resuscitation of some patients was untimely or inadequate due to the constraints and inadequacy of medical resources during the COVID-19 epidemic.\u003c/p\u003e \u003cp\u003eFrom the perspective of the disease spectrum, the incidence and death of notifiable infectious diseases in China show a more concentrated trend. The top five diseases with the highest incidence rates, such as hand-foot-mouth disease, influenza, dysentery, viral hepatitis and tuberculosis, accounted for 79.88 per cent of the total number of incidence cases, demonstrating the seriousness of these diseases in our country's infectious diseases. At the same time, the top five diseases with the highest case fatality rates of AIDS, tuberculosis, dysentery, viral hepatitis and influenza accounted for 96.56% of all deaths, which also highlights the lethality of these diseases. The incidence and case fatality rates of AIDS have been on the rise in recent decades, although China has implemented policies to strengthen AIDS publicity and education, prevention and intervention, and testing and treatment[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], which have effectively reduced the risk of transmission and fatality of AIDS, the situation of AIDS prevention and control is still serious. In our country, sexual transmission has become the main transmission route of AIDS, and we should continue to strengthen the monitoring of AIDS patients in the future, as well as strongly carry out the promotion of AIDS prevention and treatment knowledge and advocate safety behaviors[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The incidence of tuberculosis shows a significant downward trend from 2013 to 2022, which is mainly attributed to the comprehensive coverage of the direct supervision short-course chemotherapy strategy and the implementation of a series of tuberculosis prevention and treatment plans[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], but the decline during the COVID-19 epidemic may be related to the failure to provide timely diagnosis and treatment as a result of epidemic prevention and control. The effectiveness of tuberculosis prevention and control in China still has a gap with the World Health Organization's goal of ending tuberculosis by 2035, and in the future it will be necessary to strengthen focused prevention and control in areas with high incidence of tuberculosis and in the main susceptible population groups. The incidence rates of viral hepatitis (except hepatitis B) are showing a decreasing trend, and the case fatality rates (except hepatitis C) are also showing a decreasing trend. Unfortunately, the prevalence of viral hepatitis in China is still large, especially for chronic hepatitis B and C[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], so we need to further strengthen the screening and antiviral treatment for hepatitis B and C patients.\u003c/p\u003e \u003cp\u003eIn recent years, the average incidence of C infectious diseases has been on the rise, despite a 31.27% decrease during the COVID-19 epidemic compared with the three years prior to the epidemic, which was mainly caused by the high incidence of HFMD, infectious diarrheal, and influenza. Among them, the incidence of HFMD is dominated by children under 5 years of age, which requires the dissemination of knowledge about HFMD prevention and treatment to parents and teachers, as well as the reinforcement of vaccination[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. And the incidence of other infectious diarrheal diseases has continued to rise in recent years, which is consistent with the results of most studies[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Most of the epidemic outbreaks are dominated by norovirus since 2013, and the key to blocking them is to reduce environmental pollution and focus on dietary safety[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. It also shows that the incidence and case-fatality rates of influenza have increased rapidly during the last decade, with low influenza vaccine coverage being an important reason for its high prevalence[\u003cspan additionalcitationids=\"CR50\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. High incidence of the disease also increases the risk of death in specific populations, especially in people older than 60 years[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Therefore, there is a need to enhance influenza surveillance in the future along with boosting influenza vaccination rates for specific populations[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. At the same time, the emerging infectious disease COVID-19 epidemic in 2020 suggests that we need to emphasize and strengthen the effective prevention, control and close monitoring of related infectious diseases, and further promote the strength and quality of the efforts, including health education, vaccine research and development, as well as the prevention and vaccination of existing vaccines[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFrom the point of view of transmission, intestinal, respiratory, and sexual, blood and mother-to-child transmission of diseases are still the \"main force\", of which the epidemic of intestinal infectious diseases is particularly serious. Intestinal infectious diseases are mainly caused by improper hygiene habits such as eating, drinking, etc[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. The prevalence of COVID-19 has a certain impact on the incidence of gastrointestinal infectious diseases, and some studies have shown that the number of rotavirus and adenovirus-positive patients and the positive detection rate in 2020 will be significantly reduced compared with that in 2019[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. For respiratory infectious diseases, they are mainly transmitted through droplets and airborne transmission[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e], and a series of preventive and control measures taken against respiratory viruses such as COVID-19 have resulted in respiratory syncytial virus, influenza virus, adenovirus and other respiratory-transmissible viral infections being at a low level[\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. Both intestinal and respiratory spread are closely related to public hygiene habits, and the COVID-19 outbreak has not only promoted tremendous changes in people's hygiene concepts and behaviors, but also significantly improved their health literacy[\u003cspan additionalcitationids=\"CR61 CR62\" citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. In addition, blood-borne and sexually transmitted diseases showed a significant decline, particularly prominent in February 2020, followed by an oscillating rebound[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. In terms of seasonal distribution, diseases showed two peaks between 2013 and 2022, in summer and winter. Among them, intestinal and respiratory infectious diseases mainly showed some seasonality, with the onset of intestinal infectious diseases concentrated in May-July, and respiratory infectious diseases in January, June-July, and December. This may be related to the fact that high temperatures and humidity in summer facilitate the multiplication and spread of pathogens, whereas in winter, cold and dry climatic conditions favor the survival and spread of viruses.\u003c/p\u003e \u003cp\u003eIn our study, there are some limitations. Firstly, the data we used were all obtained from publicly available government information, however, the information on the regional distribution, age and gender composition of each infectious disease in these data was not comprehensive, so that we were not able to further analyze the spatial distribution of the notifiable infectious diseases, the regional differences, and the high-risk groups. Secondly, based on the data from the reporting system, we may underestimate the annual incidence rates affected by the intensity of screening. This means that, for some reasons, certain infectious diseases may not be adequately screened and therefore their incidence rates may be underestimated. Then, the incidence of certain infectious diseases may also be underestimated due to self-selection ascertainment bias, that is, people with a particular infectious disease are more likely to avoid screening than people without that infection. This implies that even if someone knows they have a particular infectious disease, they may choose not to be screened, resulting in an underestimation of the incidence of that infectious disease. Furthermore, potential biases may arise due to differences in diagnostic criteria, skill levels and laboratory conditions in different sectors or institutions, which may affect the accuracy of incidence and case-fatality reporting.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study indicates that China has made remarkable achievements in the prevention and treatment of infectious diseases. Behind these achievements are not only the aggressive engagement and scientific management of governmental departments, but also the extensive participation and joint efforts of all sectors of society. In spite of these achievements, major infectious diseases such as AIDS, tuberculosis and viral hepatitis, as well as highly prevalent infectious diseases such as hand-foot-mouth disease, influenza and infectious diarrhea diseases, are still posing a serious threat to the lives and health of the population, and the rapid spread of these diseases and the wide range of their impacts are exerting tremendous economic pressure and psychological burden on the community. More importantly, the risk of recurrence of old infectious disease outbreaks and the risk of new infectious disease outbreaks are ever-present, posing a new challenge to global public health. Therefore, we need to remain vigilant at all times, continue to strengthen the implementation of prevention and control measures, and enhance the public's health awareness and self-protection capabilities, so as to jointly safeguard the harmony and stability of society and the health and well-being of the people.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAuthors\u0026rsquo; contributions\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHR Zhou, KY Ye, N Xiao and L Ai designed the study. HR Zhou, XL Wang, Z Zhou, YF Wang and JF Hu collected the materials. HR Zhou, XL Wang and XM Wang analyzed the data. HR Zhou and XL Wang drafted the initial manuscript. GF Li, KY Ye, N Xiao and L Ai contributed to the critical revision of the article. HR Zhou, XL Wang, KY Ye, N Xiao and L Ai reviewed and edited the content of the whole paper. All authors reviewed subsequent drafts of the manuscript and approved the final version.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003e1. The Fifth Round of Discipline Leader Fostering Program of Shanghai Qingpu District Public Health System (XD2023-29)\u003c/p\u003e\n\u003cp\u003e2. Shanghai Center for Disease Control and Prevention Junior Core Component Talent Project (22QNGG28)\u003c/p\u003e\n\u003cp\u003eEthics declarations\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThe information in our study was reported by the Division of Infectious Disease, Chinese Center for Disease Control and Prevention, which is routine surveillance.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing conflict of interest.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe data come from the monthly analysis report of the National Infectious Disease Surveillance System (NIDSS) from 2013 to 2022, which was reported by the Division of Infectious Disease, Chinese Center for Disease Control and Prevention. All the other data yielded in this study are shown in the paper as well as the supplementary materials.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCassell GH, Mekalanos J. Development of antimicrobial agents in the era of new and reemerging infectious diseases and increasing antibiotic resistance. JAMA. 2001;285(5):601\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang S, et al. Epidemiological features of and changes in incidence of infectious diseases in China in the first decade after the SARS outbreak: an observational trend study. Lancet Infect Dis. 2017;17(7):716\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu Q, et al. Landscape of emerging and re-emerging infectious diseases in China: impact of ecology, climate, and behavior. Front Med. 2018;12(1):3\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl-Halhouli A, et al. 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Med (Baltim). 2023;102(39):e35316.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKessler M, et al. Health education and promotion actions among teams of the National Primary Care Access and Quality Improvement Program, Rio Grande do Sul state, Brazil. Epidemiol Serv Saude. 2018;27(2):e2017389.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChapman HJ, Veras-Estevez BA. Integrating One Health topics to enhance health workers' leadership in health promotion activities. Glob Health Promot. 2023;30(2):40\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang C et al. The Impact of COVID-19 on Consumers' Psychological Behavior Based on Data Mining for Online User Comments in the Catering Industry in China. Int J Environ Res Public Health, 2021. 18(8).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-3860619/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3860619/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo conduct an in-depth analysis of the epidemiological characteristics of 45 notifiable infectious diseases in mainland China the past decade, in order to comprehensively understand and grasp the epidemic situation, as well as to provide references and foundations for the development of effective prevention and control strategies and measures.\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e \u003cp\u003eBased on the monthly analysis report of the National Infectious Disease Surveillance System (NIDSS), data on reportable infectious diseases in China from 2013 to 2022 were obtained. The data were processed using IBM SPSS 22.0 and Excel 2010 software, and a joint-point regression model was used to analyze incidence and case-fatality ratios trends from 2013 to 2022.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eFrom 2013 to 2022, a total of 76,874,318 cases of notifiable infectious diseases were reported in mainland China, with an average annualized incidence rate of 551.26/100,000, and 207,216 deaths from notifiable infectious diseases, corresponding to an average annualized case-fatality rate of 2.70 /1,000. Throughout this period, the overall incidence rate showed a downward trend, with an average annual percentage changes (AAPC) of -0.14% (95% CI: -3.75\u0026ndash;3.51%), while the overall case-fatality rate showed an upward trend, with an AAPC of 5.41% (95% CI: 2.29\u0026ndash;8.61%). In this decade, HFMD, hepatitis B, infectious diarrhea, tuberculosis, and influenza were the prevalent infectious diseases in terms of morbidity among 45 notifiable infectious diseases, while acquired immune deficiency syndrome (AIDS), tuberculosis, rabies, infectious diarrhea, and COVID-19 were the diseases with high numbers of deaths. According to the classification of A, B and C, the incidence of notifiable infectious diseases in mainland China from 2013 to 2022 was primarily dominated by C infectious diseases, accounting for 54.50%. Based on different transmission routes, intestinal infectious diseases were the most prevalent, accounting for 40.64% of the total morbidity. The overall monthly incidence trend of notifiable infectious diseases in mainland China exhibited a \"W\" distribution, while the monthly case-fatality ratios trend shows a \"M\" distribution. During the COVID-19 epidemic period (2020\u0026ndash;2022), compared with the pre-epidemic period (2017\u0026ndash;2019), the incidence rate of 6 infectious diseases increased and the incidence rate of 34 infectious diseases decreased; the case-fatality ratios of 18 diseases increased and 14 diseases decreased.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eIt is very crucial to continuously reinforce the prevention and control of key infectious diseases, including AIDS, tuberculosis and viral hepatitis as well as highly prevalent infectious diseases, such as hand-foot-mouth disease, influenza and infectious diarrhoeal diseases. Concurrently, we should enhance our surveillance and response to emerging infectious diseases to safeguard public health and safety.\u003c/p\u003e","manuscriptTitle":"The epidemiological trends of 45 national notifiable infectious diseases in China: An analysis of national surveillance data from 2013 to 2022","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-22 18:53:22","doi":"10.21203/rs.3.rs-3860619/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a9d8f6b8-8474-419c-baa1-9b2d9062ac2c","owner":[],"postedDate":"January 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-01-24T00:43:24+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-22 18:53:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3860619","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3860619","identity":"rs-3860619","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}