Comparison of 19 major infectious diseases during COVID-19 epidemic and previous years in Zhejiang, implications for prevention measures

Located in southeast of China, Zhejiang Province is composed of 2 sub-provincial cities and 9 prefecture-level cities. It has a land area of 105,500 square kilometers and a population of about 58.5 million residents by the end of 2019. It is an economically developed province in China with a relatively well public health system [11]. As a coastal province, it has a subtropical monsoon climate with an annual average temperature of 15–18 ℃.

The data were collected from the National Notifiable Infectious Disease Surveillance System (NNIDSS), which was established by the Chinese Government and covered 1.3 billion people from all regions in mainland China [12]. According the Law of the People's Republic of China on prevention and control of infectious diseases, the notifiable infectious diseases can be divided into three categories, Class A, Class B and Class C (see Additional file 1). Since January 20, 2020, the Corona Virus Disease 2019 (COVID-19), defined as Class B infectious diseases, should be taken measures as Class A infectious diseases [13].

We collected a total of 1,821,107 incident cases of 19 notifiable infectious diseases in Zhejiang Province, from January 2017 to October 2020. We extracted the information including sex, age, occupation, date of disease onset, and date of diagnosis. Due to the fewer cases of malaria and dysentery, we combined falciparum malaria, plasmodium vivax malaria, and other malaria into malaria; and combined bacterial and amoebic dysentery into dysentery. To ensure the accuracy of the data, we excluded the data with interval longer than 30 days from onset to diagnosis, and 1,814,881 cases remained.

To control the outbreak of COVID-19, three levels of response measures have been implemented by Zhejiang Provincial People's Government. The first level response was implemented on 24 January, 2020, which was adjusted to the second level on 2 March [14, 15]. Finally, the government has carried out the third level since 23 March as the normalized prevention measures [16]. Because of the novel feature of the SARS-CoV-2, the epidemic prevention measures were mainly reflected in non-pharmaceutical interventions (NPIs). Figure 1 shows the specific events and the time when they were implemented.

In period of first level response, all the measures should be conducted under the leadership and command of the State Council. In the early stage of COVID-19, all localities focus on criteria that was internal non-proliferation and external non-export, making great efforts in closed-loop control and quantitative management, further improving the accuracy, effectiveness and coverage of control measures [14]. Besides, the important NPIs of first level response consisted of [14, 17]: (1) With advanced big data grid system, the strictest comprehensive investigation was carried out to effectively identify and cut off the source of infection; (2) Early detection, diagnosis and treatment of cases was implemented, as well as tracking management of the close contact, so as to identify and control the source of infection early; (3) The government made the adequate and force preparation on medical care and public health resources and deployed unified management to meet the basic needs of health care workers and residents for personal protection; (4) Health publicity has been strengthened, together with keeping social distances, temperature monitoring, wearing masks and hand-washing to protect the susceptible population; (5) A cordon sanitaire of Hubei province or high-risk regions were set up, and the residents who returned from other provinces need to stay at home at least 14 days, to reduce the opportunity of transmission of the virus with the mobility of people [18]; (6) To reduce the risk of exposure to the infection, all events where crowds were expected to gather were cancelled or postponed, including commercial events, entertainment venue, workplace and school reopening; (7) The Spring Festival holiday was extended to 2 February, work resumption was not as early as 9 February, and schools could be reopened in batches from 13 April, 2020 [19, 20]. Compared with the measures of first level response, the measures of second level response and third level response were relatively loose, mainly reflected in four aspects [15, 16, 21]. First, intercity travel restrictions were relaxed. In second level response, with health quick response code (health QR code), people only travelling from low-risk regions no longer needed to be tracing for 14 days, while the restrictions in Hubei province were further lifted in third level response, but still not in medium–high risk regions. Second, community restrictions were loosened. People should show health QR code, take their temperature and register the information before entering the community in period of second level response, while they could pass the community after showing their health QR code in the third level response. Third, the load capacity limitations on public transport and intercity travel were liberalized, raising the load capacity of ground public traffic from 50 to 75 percent, and the load capacity of rail transit from 50 to 65 percent in second level response. In period of third level response, public transport restrictions were released based on normalized prevention and control measures. Fourth, school reopened gradually after the epidemic of COVID-19 was under control (see Additional file 2).

The time trend of monthly incidence density and city-specific incidence density was calculated to describe the spatiotemporal distribution of diseases. City-specific incidence density (per 1,000,000 person-years) was defined as the number of total incident cases that was multiplied by the length of observation in units of year, and then divided by the population size in different cities. In order to research the epidemiological characteristic of various diseases, we also described the distribution by sex, age and occupation, and analyzed the differences of distribution of age or occupation between male and female.

We then calculated the average daily incidence of various infectious diseases in the corresponding date of three level response to observe whether the incidence of each infectious disease changed under different epidemic prevention and control stages, such as the average daily incidence from 24 January to 2 March of 2017 to 2019 corresponding to the first level response. As well, we calculated the sex-specific proportion, age-specific proportion, occupation-specific proportion, and the mean value of interval from onset to diagnosis to assess the epidemiological feature variation of infectious diseases before and after the COVID-19 epidemic in different response levels. For quantitative variables, Wilcoxon test was used to determine whether the epidemiological characteristics of each infectious diseases before the outbreak of COVID-19 was significantly different from it after the outbreak, while Chi-square test was utilized for qualitative variables.

Between January, 2017 and October, 2020, a total of 1,814,881 cases of 19 infectious diseases were reported, resulting in an average incidence of 8088.30 cases per 1,000,000 person-years (Table 1). The infectious diseases with the highest average incidence were influenza (3865.10 cases per 1,000,000 person-years), hand, foot, and mouth disease (HFMD) (2156.73 cases per 1,000,000 person-years) and other infectious diarrhea (1924.42 cases per 1,000,000 person-years), which together accounted for 98.24% (7946.25 of 8088.30 cases) of the overall incidence. Except for typhoid and scrub typhus, overall incidence of the 17 infectious diseases was highest among male individuals compared with females. The median time from onset to diagnosis of these 19 major infectious diseases was within 0–9 days, and most cases were found within their early stage of onset.

Most of infectious diseases were characterized by seasonal distribution, such as dysentery (May to September), scrub typhus (June) and influenza (January) (Fig. 2). In the whole province, HFMD presents an annual summer and winter peak; other infectious diarrheal diseases showed a semi-annual activity peak, including a major peak in winter, followed by a minor peak in summer. Haemorrhagic fever and scarlet fever show annual peak activity in summer and autumn, and SFTS also presents a semi-annual activity peak, a major peak in summer, then a minor peak occurred in autumn. Overall, the total incidence density of 8 infectious diseases varied greatly between cities in Zhejiang Province, while the total incidence of the remaining 10 infectious diseases varied less widely between different cities or too few cities. Taizhou, Hangzhou, Jinhua, Ningbo and Wenzhou are the most frequent cities with the high incidence of 19 infectious diseases. Among the 19 cities with the highest incidence of infectious diseases, Hangzhou appears most frequently (Fig. 2).

In different age groups, the sex-specific distribution was similar, the overall incidence among males was slightly higher than that among females. In different genders, the incidence of HFMD, other infectious diarrheal diseases, influenza and scarlet fever was highest among children younger than 10 years. 15 of 19 infectious diseases rhombic distributed in young and middle-aged group, except for SFTS, leptospirosis and typhus in the elderly. The incidence of 19 infectious diseases was highest among children aged 1–10 years, and lowest among the elderly aged over 75 years (Fig. 3). In different occupational group, overall incidence among male individual was higher than that among female, except for unemployment, teachers, medical staff and retirees. The incidence of 19 infectious diseases was highest among children aged 1–10 years, and lowest among the elderly aged over 75 years. Among the adult occupation, farmers had a highest incidence, followed by workers. Especially, overall incidence of scrub typhus, haemorrhagic fever, brucellosis, SFTS, and leptospirosis was higher among farmers (Fig. 4).

Since the COVID-19 was reported in January 2020, the incidence of five of 19 infectious diseases has declined precipitously, such as HFMD, hepatitis E, malaria, influenza, and scarlet fever, while the incidence of typhoid and paratyphoid became more stable after COVID-19 (Table 2). However, the incidence of SFTS and leptospirosis rose slightly. The contemporaneous incidence of paratyphoid and dengue fever did not statistically differ before and after the secondary response, and the contemporaneous incidence of scrub typhus, SFTS and rabies only statistically significantly differed before and after the third response. Besides, there was no significantly difference found in the contemporaneous incidence of leptospirosis and typhus before and after the response. The contemporaneous incidence of remaining 12 communicable diseases had statistically significant differences (P < 0.05) before and after the each of 3 level measures. In addition, the average daily incidence of 5 infectious disease increased as the relaxation of the policy. And the minimum incidence of other infectious diseases occurred in secondary response, which may be related to the lag of policy effect.

Similarly, we used the same method to assess whether the contemporaneous gender-specific incidence of 19 infectious diseases was different before and after the tertiary response, and found only the contemporaneous gender-specific incidence of influenza showed statistically significant difference before and after each level of response (P < 0.05), with the increased proportion of male individual. At the same time, the contemporaneous gender-specific incidence of other infectious diarrhea showed statistical difference before and after the primary and tertiary responses, and the proportion of male decreased. While there were no statistically differences in the contemporaneous gender-specific incidence of the other 17 infectious diseases before and after the implementation of each level of measures (Fig. 5).

We observed a significant difference of proportion of 7 infectious diseases before and after the response implement (Table 3). Among them, the age-specific proportion of HFMD, influenza and other infectious diarrheal diseases was all significantly different in three level of response. The proportion of elder than 5 years in HFMD and other infectious diarrheal diseases was on the rise, while it was opposite in influenza, dysentery, scarlet fever and typhoid.

Chi-square tests were performed for the contemporaneous occupational incidence of 19 infectious diseases before and after the tertiary response: the contemporaneous occupational incidence of other infectious diarrhea, influenza, and HFMD were statistically significant before and after each level of response (P < 0.05) (Table 4). No statistically difference was observed in terms of contemporaneous career-specific incidence of AHC only before and after the second level response. A statistically difference was observed in terms of contemporaneous career-specific incidence of scarlet fever, hepatitis e, malaria and brucellosis only before and after the first level response, and of dysentery only before and after the third level response. And we could observe that the proportion of farmers in brucellosis has descended, also in malaria, and the proportion of workers or unemployment was increased. While the proportion of farmers in AHC has increased.

The Wilcoxon test revealed that the difference in interval in most of infectious diseases before and after the response was smaller than 1 day. No statistically difference was observed in terms of contemporaneous interval of others infectious diarrhea and dysentery only before and after the first level response, and a statistically difference was observed in terms of contemporaneous career-specific incidence of typhoid and scarlet fever only before and after the first level response, and of HFMD, AHC and influenza only before and after the third level response. While there were no statistically differences in the contemporaneous interval of the other 12 infectious diseases before and after the implementation of each level of measures (Table 5).