As of April 6 ,2020 in mainland China, there were a total of 12,959 confirmed cases and 119 deaths outside of Hubei, resulting in a crude CFR of 0.90%. This CFR is lower than 5.14% (2,571/50,008) in Wuhan, China, 2.00% (73/3,654) in Japan, 1.81% (186/10,284) in South Korea, 2.72% (8,358/307,318) in the United States, and 12.32% (15,889/128,948) in Italy [1]. The success in controlling the epidemic and reducing CFR of COVID-19 patients outside of Hubei province in mainland China is remarkable. Our analysis of this phenomenon was attributed to the effective restrictive measures of the Chinese government and the relatively abundant medical resources in outside-Hubei areas. We performed descriptive analysis on the spatial-temporal distribution of all deaths outside of Hubei province. Prior to the implementation of Wuhan's lockdown policy on January 23, massive numbers of people moved across the country, especially to the surrounding provinces of Hubei, such as Henan and Hunan provinces. Daily new cases reported in Zhejiang and Guangdong provinces, which is respectively the commercial center of East China and South China and accumulate a great amount of mobile population, also showed a rapid growth trend similar to that of Wuhan. Daily new confirmed cases peaked at February 2, while daily new deaths peaked on February 12, 9 days after the peak of new cases. We speculated that the emergence of this interesting phenomenon might be related to the average duration of deaths, and the average duration from symptom onset to deaths among fatal cases was also 9 days in this study. Our result is shorter compared to another study reporting a duration of 10.56 days in Wuhan [8]. With adequate medical resources, the majority of deaths outside Hubei were cases of rapid onset and severe illness, which was likely to contribute to their shorter duration.
In this study, among the 99 confirmed COVID-19 related deaths, 59.6% were males, while 40.4% were female. Our results were consistent with an earlier study. According to an epidemiological survey of 72,314 COVID-19 patients published by the Chinese Centers for Disease Control and Prevention (China CDC) in February 2020, the number of confirmed male cases was higher than that of females (51.4% vs. 48.6%) [9]. Taking into account the composition ratio of confirmed male and female cases, the male-to-female CFR in this study was 1.43: 1, which meant that the risk of death for males with COVID-19 is 1.43 times of that for females. A recent article describing 113 deaths in Wuhan also showed that more males died than females (73.5% vs. 26.5%) [10]. Similar findings have been observed in several countries with severe COVID-19 epidemics, such as in Italy, where 70.2% of deaths are among males [11] and Spain, where 62.2% of deaths were among men [12]. South Korea, which has been touted for its epidemic response and vast number of tests, reported a somewhat similar distribution as to in our study, with 54.0% of deaths among men and 46.0% among women [13]. What is particularly noteworthy is that men died at a younger age due to COVID-19 compared to females (mean age: 69.20 vs. 74.69 years). Gender differences in smoking and the prevalence of lung diseases, diabetes, and hypertension (all of which are reportedly higher in men than in women) [14], may be a leading factor for these differences [15]. Associated with these medical conditions, men may have a higher risk of being in serious or critical condition, or even death, compared to women with COVID-19. The results show additionally that the majority of deaths were among those aged 65 years or older, which is consistent with another small-scale study in Wuhan [16]. Due to hypoimmunity or basic disease, elderly may be more susceptible to COVID-19, which potentially result in a higher risk of death [17].
According to our research, there is a significantly higher risk of death for COVID-19 infected patients living in regions of lower temperature, lower humidity, or higher latitude. Heilongjiang province, for example, is the northernmost and easternmost provincial administrative region in China, with five to six months of cold weather every year. The high prevalence of respiratory diseases such as tracheitis, emphysema, and cor pulmonale may be one of the reasons for the high CFR of COVID-19 in this region. A potential relationship between temperature, humidity and latitude and the survival and diffusion of Sars-Cov-2 has been proposed in another study [18], with COVID-19 spreading over an area roughly 30–50°N with an average temperature of 5–11℃ and absolute humidity of 4-7g/m3. It was not yet possible to judge the pattern of COVID-19 CFR at higher temperature area, as the disease was prevalent mainly in February, when the maximum temperatures of most areas in China did not exceed 20℃. But it's worth noting that areas with low temperatures, low humidity, and high latitudes should pay more attention to prevention and control and self-preservation when COVID-19 becomes prevalent again in the spring to reduce deaths, especially if COVID-19 is to coexist with us for a long time.
Lastly, we found that there was no evidence of correlation between CFR and social environment factors, such as proportion of the population aged 65 years or older, population density, or per capita GDP, which was consistent with that the outbreaks of COVID-19 in provinces outside Hubei were well managed and able to be controlled by the local health care systems. Thus, the differences in CFRs were likely due to epidemiological and clinical characteristics of the infected person. Other middle and high-income countries have showed similar outcomes. For example, Japan and Italy were both the countries with early outbreaks of COVID-19, while sharing a similar population age structure, however they appeared to have remarkable difference in CFR (3.32% vs. 10.14%). Seriously aging population and the degree of mortality in elderly population may partly explain why Italy has such a high CFR, which may also be due to how COVID-19 related death is classified, as in Italy anyone who dies and has tested positive for the disease is reported as a COVID-19 related death. In addition, the number of people tested and how confirmed cases are defined also impacts this CFR. Subsequently, the true CFR of COVID-19 will not available until widespread testing and coherent definitions are congruently used throughout countries.
This study had several limitations. First, the sample size of this study was relatively small, with less than 200 deaths confirmed outside of Hubei province. Though the findings of this study may not be generalized to other populations, they do provide descriptive trends that can be useful for informing knowledge sharing practices and creating relevant, localized policies. Second, defined as the hospital-reported deaths among confirmed COVID-19 cases, the CFR in this study does not capture deaths among all COVID-19 patients (including asymptomatic or undiagnosed infections), which could lead to inaccuracy in estimating CFR. Further expansion of testing would help provide a more reliable denominator for estimating CFR, while modeling studies may supplement these existing shortcomings. Third, ecological bias in calculating the association using population index may be present. Lastly, as many additional environmental factors could affect the CFR, false negatives might be present considering the small sample size of our study. Continual review of daily reported diagnosis and mortality data should be carried out in order to better track, evaluate, and understand the evolving and unfolding epidemic.