Evaluating the effectiveness of countermeasures to control the novel coronavirus disease 2019 in Jilin Province, China

Objective: Based on differences in populations and prevention and control measures, the spread of new coronary pneumonia in different countries and regions also differs. This study aimed to calculate the transmissibility of coronavirus disease 2019 (COVID-19), and to evaluate the effectiveness of countermeasures to control the disease in Jilin Province, China. Methods: The data of reported COVID-19 cases were collected, including imported and local cases from Jilin Province as of March 14, 2019. A Susceptible–Exposed–Infectious–Asymptomatic– Recovered (SEIAR) model was developed to fit the data, and the effective reproduction number ( R eff ) was calculated at different stages in the province. Finally, the effectiveness of the countermeasures was assessed. Results: A total of 97 COVID-19 infections were reported in Jilin Province, among which 45 were imported infections (including one asymptomatic infection) and 52 were local infections (including three asymptomatic infections). The model fit well with the reported data ( R 2 = 0.593, P < 0.001). The R eff of COVID-19 before and after February 1, 2020 was 1.64 and 0.05, respectively. Without the intervention taken on February 1, 2020, the predicted cases would reach a peak of 177,011 on October 22, 2020 (284 days from the first case). The projected number of cases until the end of the outbreak (on October 9, 2021) would be 17,129,367, with a total attack rate of 63.66%. Based on the comparison between the predicted incidence of the model and the actual incidence, the comprehensive intervention measures implemented in Jilin Province on February 1 reduced the incidence of cases by 99.99%. Therefore, according to the current measures and implementation efforts, Jilin Province can achieve good control of the virus’s spread. Conclusions: COVID-19 has a moderate transmissibility in Jilin Province, China. The interventions implemented in the province had proved effective, increasing social distancing and a rapid response by the prevention and control system will help control the spread of the disease.


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Background Coronavirus disease 2019  is caused by the novel coronavirus with typical symptoms of fever, dry cough and tiredness [1-3]. On average, the incubation period is 5-6 days from the time someone is infected with the virus to the onset of symptoms, with a maximum of 14 days [3]. Nucleic acid detection and genome sequencing have commonly been conducted with pharyngeal swabs, sputum, alveolar lavage fluid, feces, and other samples from patients to detect COVID-19 virus [4][5][6][7][8]. It has been reported that COVID-19 can be transmitted person-to-person, with the main transmission methods being either by air or contact [9][10][11][12][13]. Therefore, persons can be infected by inhaling  droplets or aerosols that are exhaled by someone with the infection, or by coming into contact with virus-contaminated items.
Due to its diverse transmission routes and strong transmissibility, COVID-19 has quickly become a global epidemic. The World Health Organization (WHO) announced that this epidemic was a public health emergency of international concern. As of April 8, more than 200 countries and regions have experienced COVID-19 outbreaks. Furthermore, the number of confirmed cases worldwide has become as high as 1,353,361 and there have been 79,235 cumulative deaths [14]. According to the report of the Chinese Health Commission, as of April 9, a total of 81,865 confirmed cases and a total of 3,335 deaths have been reported in China [15]. According to data from the Jilin Provincial Center for Disease Control and Prevention, a total of 98 cases with one death were reported [16]. On January 25, Jilin Province launched the Public Health Events level I emergency response, and took measures to control the non-resident population, such as isolation and observation at home, disinfection and sterilization, temperature measurement screening, wearing masks, etc. [17]. Since then, the epidemic in Jilin 7 / 29 Province has been checked. Although the severity of the domestic epidemic has declined, the problems of imported cases and asymptomatic cases have still been very serious.
Several studies of COVID-19 transmission models have been done to evaluate the transmissibility of the virus and predict the future situation with the epidemic [9,[18][19][20], and we have previously researched the factors of asymptomatic infection. This study is based on our previous research, adding the asymptomatic infection factor model and using the epidemic data of Jilin Province to re-verify the applicability of the model, to further discuss the role of asymptomatic infection in the spread of COVID-19 [21][22][23][24]. The more important issue at present is to consider asymptomatic infections when designing models. Asymptomatic infection refers to cases who tested positive for COVID-19 in the laboratory tests and had mild, or even no, symptoms, but can still potentially transmit the virus to others. It is estimated that at least 59% of infectious cases have not been tested [25]. If the latent of an asymptomatic infected person is different from the incubation of a symptomatic person, and the transmissibility of the two is different. then ignoring asymptomatic cases will affect the accuracy of the model. At the same time, traditional infectious disease models were built under the condition that the disease is allowed to develop [2,9,18,19,[26][27][28][29][30]. However, China declared a first-level health emergency in the early stage of the outbreak, and, with a strict supervision system and a high degree of cooperation of the people, a series of prevention and control measures, such as wearing masks, restricting travel, and suspending work and school were implemented. In this study, our COVID-19 model was established with thorough consideration of most of the possible comprehensive prevention and control measures that exist. Moreover, there is no domestic province that can be used to construct a dynamic model of the spread of COVID-19 according to the local population characteristics and 8 / 29 epidemic distribution. Hence, the transmissibility of COVID-19 in Jilin Province is still unclear and the effect of current prevention and control measures on the epidemic still needs to be explored. This study focused on the susceptible-exposed-infectious-asymptomatic-recovered (SEIAR) model based on the distribution of outbreaks in Jilin Province. The various parameters in the model were calculated based on the actual cases obtained, so it is closer to the real situation; the fit of the model to the actual data was explored, the effectiveness of current prevention and control measures was evaluated, and the progress of the epidemic without measures being taken was predicted.

Data collection
The case information collected in this article was provided by the Jilin Provincial Center for Disease Control and Prevention, including onset date, diagnosis date, date of contact with related cases, disease severity, and laboratory diagnosis of different case types. In addition, the permanent population of Jilin Province comes from the "Jilin Statistical Yearbook."
Due to the short duration of COVID-19 in Jilin Province, the number of people who were born or died of natural causes during the epidemic period can be ignored. Therefore, on this basis, we have improved the model by excluding the natural birth and natural death of various populations to construct 9 / 29 a SEIAR model of COVID-19 in Jilin Province. The model is based on the following assumptions: (1)The model divides the population into five categories: susceptible (S), exposed (E), infectious (I), asymptomatic (A), and removed (R).
(2)Both I and A are infectious, and A's transmissibility is k times that of I (0 <k <1). S may be infected when exposed to I and A, and the infection rate coefficient is β. Therefore, at time t, the infected S is βS (I + A).
(3)Among E, the proportion of those who develop asymptomatic infections is p, the incubation period is 1/, and the latent period is 1/'. Then at time t, there is p'E persons in E who develops into A, and (1-p)E persons become I.
(4) I, from onset to admission is 1 / γ days; that is, there are γ I admitted to the hospital in unit time. Therefore, at time t, there are γ I people in I who change to movers. The case fatality rate of I is f, so at time t, f I people die in I. (5)A has an infectious period of 1 / γ', that is, γ' persons in A escape from the infectious period in unit time. Therefore, at time t, there are γ' A people in A who are transformed into movers.
Therefore, the framework of the SEIAR model with the natural birth rate and mortality rate of the population removed is shown in Figure 1. The differential equations of the model are as follows:

Parameter estimation
The total number of susceptible people comes from the number of permanent residents in Jilin Province recorded in the Jilin Statistical Yearbook. According to the actual incidence characteristics of COVID-19 in Jilin Province, the cases were divided into two types: imported cases as the source of infection and secondary cases used as the actual data to fit the model. According to the trend of the secondary cases over time and using February 1 as the cut-off point, the time distribution curve of the continuation of cases was divided into two sections and fitted by the model separately, and the β value in different time periods were obtained (β 1 and β 2 ).
According to previous research by our team, the transmissibility of asymptomatic infections is the same as for infections, k = 1. There were four asymptomatic infections among 97 cases in Jilin Province, that is, the proportion of asymptomatic infections was 0.04. To calculate the time interval from infection to symptom onset in all cases in Jilin Province, except for asymptomatic infections, the median was calculated as 10. The previous literature showed that the latent period of asymptomatic infections is the same as that of typical infections [26]; therefore, =' = 0.1. The time interval from the onset to admission of infectious cases in Jilin Province was calculated, and the median was 3.
Because asymptomatic infections are mostly admitted to hospital for isolation treatment for intensive contacts, the number of infections, and the proportion of asymptomatic infections in Jilin Province are small, the period of infection of asymptomatic infections was similar to that of infections. Therefore, γ = γ' = 0.33. According to the statistics on COVID-19 in Jilin Province, there was only one death among all patients, so in the COVID-19 model for the province, the mortality rate f was negligible, that is, f = 0. The model parameter values and methods are shown in Table 1.

Transmissibility of COVID-19
Under ideal circumstances, the basic reproduction number (R 0 ) can be used to quantify the transmissibility of COVID-19 [21,[31][32][33]; R 0 is the number of cases where the source of infection directly spread the virus during the infection period. Comparing the R 0 value with 1 can be used as an index to evaluate whether the disease is prevalent. If the evaluated disease does not spread in a natural state because of the use of isolation, vaccines, and other interventions, R 0 cannot reflect the actual spread of the disease. At this time, an effective reproduction number (R eff ) is needed to represent transmissibility. Based on previous research [34][35][36], R eff can be expressed by the following equation: At the same time, because the mortality rate of COVID-19 in Jilin Province is close to 0, the equation can be simplified to:

Simulation method and statistical analysis
The software Berkeley Madonna 8.3.18 was used to model the actual cases, and the fourth-order Runge-Kutta method was used to solve the differential equations. Curve estimation in SPSS 20.0 was used to compare the fitted data with the actual data, and observe the P and R 2 values to judge the goodness of fit.

Epidemiological characteristics
As of March 14, a total of 97 COVID-19 infections, including 45 imported infections (including one asymptomatic infection) and 52 secondary infections (including three asymptomatic infections), were reported. The first case in Jilin Province was an imported case whose onset date was January 12, 2020, while the most recent case was a secondary case whose onset date was February 9, 2020. The peak date of the incidence of imported cases was January 22, and the peak of local cases was February 1. The stacked histogram of changes is shown in Figure 2.
Regarding the gender breakdown (Figure 3), there were 56 males and 41 females. Among male and female cases, normal cases predominated, accounting for 54% and 49% of all case types, respectively. In descending order, these were followed by mild, severe, and critical cases.
The proportion of disease severity of different age groups was analyzed ( Figure 4). The age of onset was concentrated between 20-59 years, accounting for about 80.41% of the total number of patients. Among all reported cases, the proportion of mild cases in the 40-49 age group was 56%, the proportion of normal cases in the 30-39 age group was 73.33%, and the proportion of severe cases in the 80-89 age group was 33.33%, the proportion of critical cases in the 70-79 age group was up to 20%.
The proportion of normal cases was highest in different age groups, and the number of cases decreased as the severity of the disease increased.

Model fitting and calculation of transmissibility
According to the comparison between the model fitting curve and the actual secondary cases curve ( Figure 5), the degree of fitness was good. At the same time, the goodness-of-fit test results 13 / 29 showed that the difference between secondary cases fitted by the model and the actual secondary cases was statistically significant (R 2 = 0.593, P <0.001). The values of β 1 and β 2 obtained by the model fitting were brought into the formula of the effective reproduction number. The effective reproduction number of COVID-19 cases before February 1 was 1.64, the effective reproduction number of COVID-19 cases after February 1 was 0.05;the transmissibility decreased by 96.95%.
It is known that after February 1, the incidence of COVID-19 showed a downward trend, and the last case occurred on February 19 ( Figure 2). If no intervention measures had been taken after the onset of new coronary pneumonia, the model can fit the curve of the future incidence in this scenario ( Figure   6). The model predicted that if no measures had been taken, the incidence on February 19 would have been 13 cases, while the actual incidence on that date was one case. Therefore, the comprehensive interventions reduced the incidence by 92.31%. If the epidemic situation had been allowed to continue, the incidence curve would resemble a bell shape, and it would reach its peak on  (Table 3). actual incidence has been decreasing. Since January 31, 2020, the implementation time of intervention measures such as reducing travel and wearing masks has been consistent with the incidence decline time. This shows that the above intervention measures were effective during this period.

Discussion
The clinical disease types of COVID-19 in Jilin are the most common cases [37], and are consistent with the distribution of clinical types in the whole country. This shows that most cases are mild and as easily treated by patients as common influenza. For this reason, it has been difficult to investigate who infected persons have had close contact with. Therefore, a large number of sources of infection were not effectively isolated in the external environment at the early stage of the disease and at the early stage of the epidemic, which was the main reason for the public response delay in the early stage of the outbreak.
The age of onset of COVID-19 in Jilin was mainly between 20-59 years. Among these cases, people aged 30-49 years most commonly had mild and normal cases [38]. Therefore, among young adults and middle-aged, the prognosis of the disease is better and mortality is low.
In In the early stage of the outbreak, our team developed a Bats-Hosts-Reservoir-People transmission network and assessed the human-to-human transmissibility of COVID-19 in Wuhan to be 3.58 [21].
Studies have been done on the transmissibility of COVID-19 in different provinces and cities in China at different time periods, which found that the reproductive number ranged from 1.4 to 6.49, with a median of 2.79 in 12 studies [39]. Yousef Alimohamadi et al. used systematic reviews and meta-analysis to estimate the pooled R0 to be 3.32 (95% CI, 2.81 to 3.82) [40]. Salihu S Musa and others estimated that the R 0 of COVID-19 in Africa was 2.37 [41]. J Smith Torres-Roman et al. beginning of the outbreak, there are some cases that were onset but had not been detected and reported.
The incompleteness of the popularity curve may cause R 0 to become higher [40]. At the same time, the low number of early disease incidences and the uneven quality of case reports may contribute to the difference in R 0 [42], showing that the more complete the data when estimating the transmissibility of infectious diseases, the more conducive it is to accurate research results.

Limitations
The In this study, the reciprocal of the incubation period calculated using the actual data of the COVID-19 spread in Jilin Province was a parameter in the model, so the accuracy of the incubation period calculation can also affect the model's prediction. The incubation period of COVID-19 is 5-6 days [43], and the incubation period of the disease calculated in this study was 10 days in Jilin Province.
The reason may be that the time of contact with the first case is uncertain, and there are some cases with unclear contact time, such as repeated or continuous contact. Therefore, it is necessary to clarify the activity trajectory of secondary cases, or how long susceptible persons have the ability to infect others after being exposed to the source of infection. This is also a direction for exploration in future research.
In accordance with the epidemic trend of the disease, this study fitted the actual number of secondary cases in two stages. Additionally, the transmissibility of COVID-19 after February 1 was evaluated, and the effectiveness of preventive measures was verified. However, this article evaluated comprehensive prevention and control measures, but did not evaluate specific measures. It is not possible to determine which specific measure produced an effect. To solve this problem, it will be necessary to establish a model that considers individual prevention and control measures. However, the specific implementation time and completion status of each measure are difficult to determine, so this is likewise difficult to achieve.

Conclusions
COVID-19 had moderate transmissibility in Jilin Province, China. The interventions implemented in the province were highly effective; increasing social distancing and a rapid response by the prevention and control system will help control the spread of the epidemic.

Ethics approval and consent to participate
This effort of disease control was part of CDC's routine responsibility in Jilin Province, China.
Therefore, institutional review and informed consent were waived by the Ethics Committee of Jilin Provincial Center for Disease Control and Prevention. All data analyzed were anonymized.