COVID and Gender in Asia-Pacific Region: History
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The COVID-19 pandemic has been the largest infectious disease epidemic to affect the human race since the great influenza pandemic of 1918-19 and is close to approaching the number of deaths from the earlier epidemic. The data on COVID-19 shows that the rate of clinical cases is about 10% greater in females than males in Asia. The number of deaths is greater in males than in females. Women are more likely to experience the psychological effects of COVID-19 during and after acute infections.

  • COVID-19
  • gender
  • women’s health
  • pandemic
  • long COVID
  • Asia

1. Introduction

The COVID-19 pandemic has been the largest infectious disease epidemic to affect the human race since the Great Influenza Pandemic of 1918-19. Estimates of the number of deaths in the influenza epidemic range as high as 100 million, but a figure of 50 million is more probable [1]. As of November 2022, the number of global deaths due to COVID-19 that have been recorded is 6.6 million [2].
The deaths reported to WHO are very likely to be underestimated, as many cases of COVID-19-related deaths go unreported and this can be assessed by monitoring excess mortality. In the pandemic up to the end of 2021 WHO had recorded 5.4 million deaths and estimated that excess mortality during this period accounted for a further 9.5 million deaths. This brings the total number of deaths associated with COVID-19 to 14.9 million [3]. Extrapolating the data to November 2022 suggests that the true number of deaths is likely to be closer to 18.1 million. The advent of vaccinations against COVID-19 is estimated to have averted approximately 20 million deaths by the end of 2021 [4]. If the actual number of deaths and the number of deaths averted are considered together, the total is comparable to the Great Influenza Epidemic. When the experience of 2022 is included, COVID-19 may be the greatest epidemic of all time. The WHO estimates for excess mortality in the South East Asia and Western Pacific regions were 5.99 (40.2% of global excess mortality) and 0.12 million, respectively [3].
The pre-COVID-19 world was one in which gender equality was not yet the norm. Inequality has been worsened by the pandemic. Discriminatory patterns exist in terms of access to, ownership and control of productive resources Relative income poverty, physical vulnerability, and lack of fully equitable and meaningful participation at all levels of decision-making processes have worsened. This is particularly the case for minority groups and indigenous women in Asia [5].

2. COVID-19 Cases and Deaths

Data on the incidence of COVID-19 have been collected by national public health ministries and organisations and have been consolidated by the World Health Organisation and other independent programs. The WHO uses the term ‘confirmed cases’ (see above), and as of the end of October 2022, it has recorded 627 million cases and 6.6 million deaths [2]. Results that are almost identical are reported by the Johns Hopkins Coronavirus Resource Center [16]. Totals are regularly updated, but COVID-19 gender data are incomplete.
COVID-19 data disaggregated by gender are provided by the Sex and Gender COVID-19 Project a partnership of Global Health 50/50, the African Population and Health Research Center (APHRC), and the International Center for Research on Women (ICRW) and is funded by the Bill and Melinda Gates Foundation [17]. However, gender-disaggregated data are difficult to interpret due to the lag in data reporting and the lack of gender information in most of the data. The available data are shown in Table 1.
Table 1. COVID-19 Cases and Deaths by Gender ASIA (Selected Countries).
In the table above there are some discrepancies between the figures from Global Health and the WHO due to different reporting dates and the completeness of the data. Gender is often missing, or reported at a different time, from other COVID-19 data and the gender distribution data may reflect this. The data from Australia, Japan, Korea, New Zealand, Taiwan and the USA for cases and deaths are regarded as complete.
In Table 1. in Asia, female cases are recorded as approximately 10% greater than males in the countries with more complete data, but the number of deaths is about 20% lower. The case fatality rate, the proportion of confirmed cases who died, was approximately 20% lower in females.
As well as the large national databases a large number of small case series have been published and subsequently included in meta-analyses. A meta-analysis of 3.1 million cases from 100 studies found that there was no difference in gender in contracting a COVID-19 infection [19]. However, males had higher mortality (OR 1.39; 1.31, 1.47) from COVID-19 and were more likely to be admitted to ICU (2.84: 1.45,3.79). This study included three reports from Asia, all from China. A further meta-analysis of 41 studies, including 18 from China, found that male sex, older age, obesity, diabetes and chronic kidney disease were associated with higher rates of mortality [20]. Both meta-analyses used data from the early stages of the pandemic. A more recent review that added studies from 2021 to previous analyses confirmed that the male sex was associated with increased mortality, admission to ICU and other severe outcomes [21]. In a scoping review of COVID-19 and gender in China, Feng concluded that more research is needed on gender and such an important disease [22].
Global excess deaths associated with COVID-19, have been modelled by WHO. In the following Table 2, the data from selected Asian countries are shown.
Table 2. COVID-19 Excess Deaths by Gender in selected countries of ASIA.
The WHO has developed protocols for documenting COVID-19 cases, including asymptomatic infections and vaccination effectiveness through serology surveys [23]. The data are consolidated on the SeroTracker Dashboard [24,25]. A global seroprevalence survey included surveys from three Asian countries that found no gender difference in prevalence [26]. In the future, it is likely that serology surveys will be used more often to monitor the epidemic.
The hospitalisation rate varies considerably according to the availability, accessibility and affordability of hospital beds. The data available for COVID-19-related admissions in Asia were limited. It reflects local accessibility more than other factors.

3. Life Expectancy

This is the best overall single statistical measure of health and is now becoming available for the COVID era. Life Expectancy changes since the onset of the COVID-19 pandemic have been documented in 29 countries [27]. Changes in estimated life expectancy in the past 2 years are attributed to the pandemic. Only a few countries for which data are available did not have declines in life expectancy in 2020, including Norway, Denmark, Finland (for females only), New Zealand and Australia. Since 2020 countries in Western Europe have shown a recovery of life expectancy losses, but Eastern Europe and the United States continue to have life expectancy deficits [27]. In the USA the decrease in life expectancy undoes all of the gains in the last 26 years [28]. The Schöley review was unable to include analyses from lower and middle-income countries due to data limitations, but early studies of the pandemic from India suggest that there will be a substantial downturn in life expectancy there [29,30]. At this time, data on life expectancy changes in the Asian region are limited, but the available data are shown in Table 3.
Table 3. Life Expectancy Changes in the COVID-19 era.
The data currently available show that the gap between females and males in life expectancy has increased during the COVID-19 pandemic as males have had higher death rates from COVID-19. The most severe decline in period life expectancy so far documented in the USA where it is estimated that it has declined to the levels seen in 1996. The last time such a large drop in life expectancy occurred was during the 1918 Influenza Epidemic.

4. Long COVID-19

In the absence of definitive diagnostic tests, the documentation of long COVID-19 prevalence by gender is difficult and is dependent on assessing symptoms and the level of daily functioning, usually 3 months after the onset of the acute disease. It has a substantial impact on communities because of the loss of productivity at all levels of the economy and in the family. The commonly used definition in general use is “the condition that occurs in individuals with a history of probable or confirmed SARS-CoV-2 infection, usually 3 months from the onset of COVID-19, with symptoms that last for at least 2 months and cannot be explained by an alternative diagnosis” [38].
Estimates of the prevalence of Long COVID-19 show considerable variation with a range in prevalence from 9% to 81% in different studies, which is not surprising given the lack of a definitive diagnostic test [39]. A meta-analysis of 50 studies including 1.7 million subjects found an incidence of Long COVID-19 of 43% (95%CI 39,46%), 54% in subjects who had been hospitalised [40]. In Asia, the prevalence was 51% (95%CI 37,65%), higher than in Europe and the USA. This study also found that the female sex and pre-existing asthma had a higher proportion of post-COVID-19 conditions. Other chronic conditions are also likely to predispose to long COVID-19 with rates. Aiyegbusi also found an increase in symptoms in females but noted the need for better controls and gender-matched studies [41]. In a prospective cohort from Italy, females were found to be associated with a higher risk of developing “long COVID-19”, together with older age and smoking [42].
Further reviews which do not provide regional data also found that the likelihood of having long COVID-19 syndrome was higher in females, and they had a higher prevalence of psychiatric (depression), ear, nose and throat, and musculoskeletal and respiratory symptoms [39]. Mental health symptoms are a common feature of long-COVID-19 syndromes, including depression, sleep problems and fatigue and have a higher prevalence in women [43]. A review by Maglietta found significant associations between long COVID-19and female sex with any symptoms (OR 1.52 95% CI 1.27, 1.82), with mental health symptoms (OR 1.67 95% CI 1.21.2.29)and with fatigue (OR 1.54, 95% CI 1.32–1.79); and acute disease severity with respiratory symptoms (OR 1.66, 95% CI 1.03–2.68) [44] Long COVID-19 is also associated with many pre-existing conditions, including chronic obstructive pulmonary disease, fibromyalgia, anxiety, and coeliac disease, in addition to risk factors such as obesity, tobacco smoking, being female, and socioeconomic deprivation [45,46].
Children can also experience post-COVID-19 symptoms, and there are some reports that the prevalence of psychological complications is higher in female adolescents. A small cohort study of children from more than 120 days after their COVID-19 infection from Italy found 42.6% being impaired by these symptoms during daily activities 120 days after COVID-19, and no gender differences [47]. A review of the impact of the pandemic on children documented substantial negative impacts on their mental health. As well as during acute infection, COVID-19 has effects through illness and absence of care and social isolation during school closures and community lockdowns. These events caused relatively high rates of depression, anxiety, stress and post-traumatic stress disorder (PTSD) and suicidal behaviour. Adolescents had more of the psychological impact compared to children and female adolescents were at higher risk of experiencing anxiety, depression, and stress [48].
Vaccination is probably protective against developing long COVID-19. A cohort study of 3000 subjects in the UK given two doses found that 9.8% (CI 8.1, 10.6%) developed symptoms of long COVID-19 after 120 days. compared to 14.5% (CI 13.4, 15.9%) in controls [49]. When a vaccine was administered after contracting COVID-19, a first vaccine dose was associated with an initial 12.8% decrease (95% CI 18.6, 6.6%) in the odds of developing long COVID-19 [50], although others have found different results and further studies are needed [51].
In summary, long COVID-19 is at present difficult to diagnose and quantify empirically and women have a 10–20% higher rate than men. Full vaccination levels offer some protection.

This entry is adapted from the peer-reviewed paper 10.3390/ijerph20010245

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