Skip to main content

COVID-19 pandemic in Taiz Governorate, Yemen, between 2020 and 2023

Abstract

Background

The coronavirus disease 2019 (COVID-19) is highly contagious and causes a series of health problems, particularly in Yemen, which has a fragile healthcare system and cannot handle public health emergencies.

Aims

This analysis aimed to determine the epidemiological status of COVID-19 in the Taiz governorate between April 2020 and December 2023.

Methods

A retrospective study based on surveillance data from the Taiz governorate was used. The required data were gathered from the Ministry of Health and Population in Aden and analyzed using SPSS.

Results

Out of 5826 suspected of COVID-19 cases, 1933 (33.18%) cases were positive for COVID-19 infection. The high rates of COVID-19 cases were reported at 35.40% in males, 37.80% in people aged 35–44 years, 47.20% in 2020, 72.73% in Dhubab district, and 27.78% in March 2021. The overall incidence rate of cases was reported at 6.2 per 10,000 people in Taiz governorate (8.85 in males and 3.80 in females). In addition, the high incidence rate of COVID-19 was observed among age groups ≥ 65 years, in 2021, and in Al-Mukha districts. In total, the rate of fatality cases was 14.12%, the higher rate of fatality cases was 15.46% among males and 32.23% among individuals aged ≥ 65 years, and 26.97% in 2020.

Conclusion

In this finding, the incidence rate of COVID-19 is high. It is necessary to increase the public’s awareness of the transmission and prevention methods of COVID-19, as well as implement appropriate strategies to protect populations from infectious diseases.

Peer Review reports

Introduction

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is the infectious virus causing Coronavirus Disease 2019 (COVID-19). This virus is rapidly transmitted among individuals via air droplets or aerosols that result from the coughing, sneezing, speaking, singing, or breathing of infected or carrier individuals [12]. The symptoms of COVID-19 vary from mild symptoms to severe illness. Fever, headache, anosmia, ageusia, congestion and runny nose, sore throat, cough, muscle pain, diarrhea, and difficulty breathing are the common symptoms [3]. The first reported case was in Wuhan city, China, in December 2019 [4]. Since the outbreak began, over 772 million confirmed cases and 6.9 million deaths have been reported worldwide [5]. Additionally, according to estimates by the World Health Organization, the number of deaths directly or indirectly attributed to the COVID-19 pandemic is approximately 15 million [6].

Older individuals and males over the age of 70 are at a higher risk of infection and severe disease. Adolescents seem to be as susceptible to infection as adults, and children are less susceptible [7]. Children, unlike adults, don’t seem to be more vulnerable to serious disease based on sex or age [8]. Variants of viruses can spread faster and more easily among young children than wild-type viruses, but less people have been hospitalized [9].

On April 10, 2020, the first confirmed case related to the COVID-19 epidemic in Yemen was announced, with the incident in the Hadhramaut [10]. According to the WHO report on Yemen, more than 11,000 cases and 2,159 deaths were recorded to date. The COVID-19 case fatality rate in Yemen reached a peak of 22.6%, despite the low global fatality rate of 1.0% [5].

The high number of cases and deaths in Yemen may go beyond what the authorities claim. This is due to the fact that Yemen still faces numerous challenges, including political instability, armed conflict, and humanitarian situations [5, 11].

Furthermore, in Yemen, as in other low-income countries, the epidemiological pattern of COVID-19 is uncertain because of the war since 2015, which devastated the healthcare system in Yemen. In addition, there is no surveillance or laboratory capacity, insufficient public health resources, and insufficient financial resources, treatments, or vaccines [12]. Only a few studies have been conducted in certain regions of Yemen. A study conducted in Sana’a, from June 2020 to January 2021 and revealed that the seroprevalence of COVID-19 was reported at 51.4% among suspected patients [13]. In Aden 2020, the pooled seroprevalence of COVID-19 was 27.4% [11]. In addition, the overall frequency of COVID-19 was 94.3% among healthcare workers in the Lahj and AL-Dhalea hospitals [14].

To our knowledge, no previous studies have been undertaken regarding the epidemiological pattern of the COVID-19 pandemic in Taiz, Yemen. Therefore, this analysis aimed to determine the epidemiological patterns of COVID-19 in the governorate of Taiz between April 2020 and December 2023.

Materials and methods

Study design

A retrospective study based on surveillance data of Taiz governorate was used. Taiz governorate is located in the southwest of Yemen and is 280 km from Sana’a, the capital of Yemen. It has a total area of 12,605 km2 with a total population of 3,309,546 individuals. Taiz governorate is connected to the governorates of Al-Hudaydah and Ibb from the north, some parts of Ibb, Al-Dhale’e, and Lahj governorates from the east, Lahj governorates from the south, overlooking the Red Sea coast and directing the Bab Al-Mandab. The western part of Taiz has a hot, humid, and arid climate, while the eastern part has a moderate to cold and humid climate. The governorate is divided administratively into 23 districts (Fig. 1).

Fig. 1
figure 1

Map of Taiz governorate

Data collection

The data was collected by surveillance staff, it was for all suspected and confirmed cases reported electronically to the Ministry of Public Health and Population during the period between April 2020 and December 2023. A soft copy of surveillance data in an Excel sheet format was obtained from the Ministry of Health and Population in Aden. The data contained the following variables: the number of weekly infections, the month and year of infection, sex, the age groups, the name of the district, and the result of COVID-19 tests by polymerase chain reaction test (PCR) performed in the AL-Gumhorri hospital and the National Center for Central Public Health Laboratories-Taiz branch. Based on the epidemiological monitoring system, the variables were categorized into subgroups. Eight age groups for those involved were: ≤5, 5–14, 15–24, 25–34, 35–44, 45–54, 55–64, and > 65 years.

Data analysis

All COVID-19 cases that came from Taiz governorate residents, completed information, and subjected to laboratory analysis by polymerase chain reaction (PCR) were included in this analysis. On the other hand, all cases from people who did not live in the Taiz governorate, did not have complete information, or were not subject to laboratory analysis were excluded from the analysis.

The positivity rate of COVID-19 was calculated by dividing the number of confirmed cases by the total number of tested cases.

The population denominator was obtained from OCHA [15] and used to calculate the incidence rate (per 10,000 population) based on the following formulation:

$$\eqalign{& {\rm{Incidence}}\,{\rm{rate}} \cr & {\rm{ = }}\,{{{\rm{Total}}\,{\rm{number}}\,{\rm{of}}\,{\rm{confirmed}}\,{\rm{COVID - 19}}\,{\rm{cases}}} \over {{\rm{Total}}\,{\rm{number}}\,{\rm{of}}\,{\rm{population}}\,{\rm{size}}\,{\rm{at}}\,{\rm{risk}}}} \cr & {\rm{*}}\,{\rm{10,000}} \cr} $$

The Case Fatality Rate (CFR) was calculated according to follow formula:

$$\eqalign{& {\rm{CFR}}\,\left( {\rm{\% }} \right) \cr & {\rm{ = }}\,{{{\rm{Number}}\,{\rm{of}}\,{\rm{deaths}}\,{\rm{from}}\,{\rm{COVID - 19}}\,{\rm{cases}}} \over {{\rm{Number}}\,{\rm{of}}\,{\rm{confirmed}}\,{\rm{cases}}\,{\rm{of}}\,{\rm{COVID - 19}}\,{\rm{cases}}}} \cr & {\rm{*}}\,{\rm{100}} \cr} $$

Statistical analysis

Descriptive statistics: frequencies and percentages were used to present the quantitative variables in tables and figures. In addition, the statistical package for social sciences (SPSS) program was used to calculate the confidence interval (95% CI) and chi-square test (χ2) between variables. A probability (P) value was considered statistically significant at ≤ 0.05.

Results

Demographic characterizations and positivity of COVID-19 cases

Between April 2020 and December 2023, a total of 5826 suspected COVID-19 cases enrolled in the surveillance were tested by molecular method. They were almost from all districts and all age groups with the highest proportion of 29.1% and 21.49% from Al Mudhaffar district and people > 65 years., respectively. Nearly two-thirds 62.12% were males and 58.07% were reported in 2021. The overall positivity rate of cases was 33.18% (1933), it was higher among males (35.40%) compared with females (29.54%). A higher rate of COVID-19 cases was observed in the 35–44 years (37.80%), followed by the 25–34 years (36.50%), and 45–54 years (33.79%) age groups. In addition, a lower rate of COVID-19 cases was in the aged 5–14 years (19.75%). Regarding the year of infection, the highest rate of cases was in 2020, and the lowest in 2023. The highest rate of COVID-19 cases was from Dhubab (72.73%), At Ta’iziyah (71.43), Al Mukha (58.94%), and Shara’b As Salam (52.94%) while there no data about COVID-19 cases reported in Hayfan and Mawiyah districts, as listed in Table 1.

Table 1 Demographic characterizations of suspected and confirmed COVID-19 cases

Figure 2 shows that the highest proportion of COVID-19 cases was recorded in March 2021 (27.78%), followed by April 2021 (21.93%), June 2020 (9.47%), May 2021 (8.17%), and January 2022 (5.59%). The lowest rate was noted in November and December 2020 (0.05%) with statistical differences (P = 0.001).

Fig. 2
figure 2

Monthly trends of COVID-19 cases in Taiz between April, 2020 and Dec, 2023

Figure 3 shows that a greater number of COVID-19 cases were documented in week no. (13) in 2021, with 212 cases followed by Week No. (24) in 2020, with 74 cases in Week No. (4) in 2022, with 55 cases and week No. (12) in 2023 for five cases.

Fig. 3
figure 3

Cumulative weekly trends of COVID-19 cases in Taiz between April, 2020 and Dec, 2023

Incidence rate of COVID-19 according to demographic factors

In this finding, the total incidence rate of COVID-19 was reported at 6.2 per 10,000 people in the Taiz governorate. According to the results based on sex, the incidence rate of cases was 8.85 per 10,000 individuals among males compared with 3.80 per 10, 000 individuals among females. Similarly, the highest incidence rate of COVID-19 infection was detected in the age group ≥ 65 years, followed by the age groups of 55–64 years (25.55) and 45–54 years (14.93), and a lower rate was observed among the age group of ≤ 5 years (0.05). In addition, the highest incidence rate of COVID-19 was documented at 4.52 per 10,000 people in 2021, followed by 1.00 per 10,000 people in 2020, 0.65 per 10,000 people in 2022, and 0.05 per 10,000 people in 2023, as summarized in Table 2.

Table 2 Incidence rate of COVID-19 according to socio-demographic parameters in Taiz governorate

Regarding the district under investigation, the highest incidence rate of COVID-19 was reported at 49.44 per 10,000 people in Al Mukha, followed by 40.20 per 10,000 people in Mashra’a Wa Hadnan, 32.60 per 10,000 people in Al Mudhaffar, 22.84 per 10,000 people in Salh, 22.25 per 10,000 people in Al Qahirah, and 21.38 per 10,000 people in Al Mawasit while the other district was less than 7.0 per 10,000 people (Fig. 4).

Fig. 4
figure 4

Trend of incidence rate of COVID-19 concerning district in Taiz between April, 2020 and Dec, 2023

Case fatality rate of confirmed COVID-19 cases

Among the 1933 COVID-19 cases, the overall case fatality rate was 273 (14.12%). The fatality rate was significantly higher among males (15.46%) than females (11.50%). The older age group of ≥ 65 years had the highest fatality rate (32.23%), followed by those aged 55–64 years (26.86%) and 45–54 years (14.33%). Whereas, the 15–24 years age group had the lowest fatality rate (0.69%). The fatality rate increased to 26.97% in 2020 and gradually decreased to 12.75% and 5.75% in 2021 and 2022, respectively. Regarding the location of cases in distracts, the Shara’b Ar Rawnah district reported the highest rate of fatality (66.67%). More than one-third of the rates were 37.93%, 36.51%, and 33.33% in Al Ma’afer, Jabal Habashy, and Al Mawasit, respectively. Additionally, less than one-third of the fatality rates were in Ash Shamayatayn (29.52%) and Dhubab (25%). However, a lower rate was in the Al Wazi’iyah (2.7%) and Al Mukha (1.25%) districts (Table 3).

Table 3 Frequency of case fatality rate of COVID-19 in Taiz governorate

Discussion

To our knowledge, this analysis is the first one conducted in Yemen, particularly in the Taiz governorate. From April 2020 to December 2023, 5826 COVID-19 cases were included in this work and only 1933 cases were positive for COVID-19 infection by molecular techniques. In the current results, the prevalence of cases was observed to be significantly higher among males (35.40%) as compared to females (29.54%). Similar reports have been conducted in different countries in the world showing COVID-19 infections are more in males than females [16,17,18,19,20]. These data were in disagreement with the results of several studies [11, 14, 21].

Females have stronger immune systems, including antiviral interferon and humoral and adaptive immunity that fight against viruses, particularly SARS-CoV-2 infections [22]. The results of the 2017 research revealed that female mice were less susceptible to the SARS-CoV virus than their male counterparts. However, after having an ovariectomy, the differences between genders’ vulnerability to the virus disappeared. This means that estrogen may have been responsible for the differences in vulnerability [23].

In addition, the X-chromosome in women, unlike the Y-chromosome in men, contains the majority of immune-associated genes, giving them a stronger immune system. Males having higher levels of angiotensin-converting enzyme-2, the primary SARS-CoV-2 receptor, than females [2425].

At the beginning of the 2019 pandemic COVID-19 outbreak, most COVID-19 cases were observed among elderly individuals [26]. The age groups 35–44 had the highest proportion of COVID-19 cases (37.80%), while those aged 5–14 years (19.75%) had the lowest rate. These results were different from a study that found more cases of COVID-19 cases were more prevalent in the older people than the younger people [16, 2021]. On the contrary, a study by Sallam et al. [13] found a higher rate of COVID-19 cases among the age group of subjects aged 19–49 years. Similarly, the highest frequency rates were observed among the age group of 15–29 years [11]. In Australia, adults aged 20 to 29 have a higher infection rate [27].

Older individuals are more vulnerable to COVID-19 and are at a meaningfully increased risk for morbidity and death [28]. Infections in older adults frequently manifest in an atypical manner, thereby complicating their identification and management. The physiological changes associated with old age, several age-related co-morbid diseases like diabetes and heart and lung disease, and the use of related medications are all factors contributing to poor health status [24].

Regarding the period of infection, the highest rate of cases was in 2020, and the lowest in 2023. This outcome was supported by some reports [2930]. The continuous conflict in the governorate since 2015 that led to the destruction of the healthcare infrastructure, increased poverty, inadequate health resources, and the escape of healthcare staff to another area are all factors contributing to the increase in COVID-19 cases in 2021.

Recently, the Worldometer reporting COVID-19 in Yemen revealed that the high cases were reported at 119, 178, and 245 cases, respectively, in June 2020, April 2021, and January 2022 [31]. These data are similar to our results showed that a high rate of COVID-19 cases was recorded at 9.47%, 27.78%, and 5.59% in June 2020, March 2021, and June 2022, respectively. COVID-19 has been reported in Yemen in three waves as of 3 January 2022: the first wave occurred from April to July 2020, the second wave occurred from February to May 2021, and the third wave occurred between August and October 2021 [32].

Four waves were the result of the global COVID-19 pandemic: the first, which lasted from January 2020 to February 2021; the second, which lasted from March 2021 to June 2021; the third, which lasted from July 2021 to October 2021; and the fourth, which lasted from November 2021 to March 2022 [29].

The seasonal trends in COVID-19 cases were estimated to be between November and April for all outcomes and in all countries [33]. Many viruses that infect the respiratory system have different patterns during the winter months [34]. It is widely acknowledged that factors such as the host, pathogen, and environmental factors, such as an increase in indoor activity and seasonal weather fluctuations, have a significant impact on the viral stability beyond the host [35].

In this finding, the overall incidence rate of COVID-19 was 6.2 per 10,000 people in Taiz. A report by Lai et al. [36] found that the incidence varied from 0.0002 per 1,000,000 populations in India to 61.4 per 1,000,000 populations in Korea. According to the results based on sex, the high incidence rate of COVID-19 was higher among males compared with females. This finding is similar with previous reports [11, 14, 21]. Similarly, the highest rate of COVID-19 infection was noticed among age group ≥ 65 years and the lowest was found among age group of ≤ 5 years and this finding is in consistent with early research [15, 1920]. In addition, the incidence rate of COVID-19 was highly increased in 2021 and decreased in 2023. This finding is supported by a previous report [37]. This decrease in the COVID-19 pandemic in the study area may be due to factors such as adherence to COVID-19 preventive measures, progress of vaccination campaigns to achieve herd immunity (population immunity) in Yemen, and stopping flights and land ports to and from Yemen. These factors may play important roles either directly or indirectly in reducing and controlling the COVID-19 pandemic in Yemen.

Furthermore, The Al Mukha district exhibited the highest incidence of COVID-19. This could be attributed to the fact that the majority of the nearby residents were moved to the Al Mukha district during the armed conflict.

This finding revealed an average 14.12% rate of fatality cases. Recently, the overall case fatality rate was 22.9% in Yemen [5]. Globally, the case fatality rate was recorded at 1.0% [5]. The case fatality rate was reported at 2.3% in China [16] and between 3.3 and 4% in Africa [19, 38], 0.16% in Australia [27], 2.92% in Germany [38], 1–20% in Ethiopia [39], and 3.72% in Latin America [40].

The present data showed the fatality rate was significantly higher in males (15.46%) compared to females (11.50%). This result aligns with the recent findings that documented that the fatality case rate was higher in males than females [16, 4041].

The fatality rate was higher among individuals aged ≥ 65 years. This finding is in agreement with the results of previous studies [16, 42]. COVID-19 is more likely to cause serious illness or death in older adults if they are unvaccinated, have a disability, have an impaired immune system, or have certain medical conditions. Therefore, they are more likely to need hospitalization, intensive care, or a ventilator breath; otherwise, they may succumb to death [43].

Limitations of this study

This work has several limitations. First, there are no data on COVID-19 cases in the Mawiyah and Hayfan districts, which are under the control of the Sana’a authorities, and this is considered the most important limitation. Second, some cases were clinically diagnosed as being infected with COVID-19 but without laboratory confirmation and were excluded from this data anlysis. Third, there is a weakness in the data documentation and recording in health centers, which is another limitation of this work.

Conclusion

The high incidence rate of COVID-19 infection in the study area may be due to the fragile health system resulting from the continuing armed conflict and a lack of financial resources. Health institutions must establish awareness efforts and adopt modern communication methods to raise the community’s knowledge and effective practices for COVID-19 prevention. In addition, it is necessary to establish epidemiological surveillance centers to control and prevent emerging diseases such as COVID-19 through follow-up on implementing effective vaccination programs in the community. Additionally, encouraging the conduct of studies and research as well as the early detection of emerging communicable diseases will encourage the decision-maker to implement strategies that are effective in protecting populations from infectious diseases.

Data availability

The datasets used and analyzed during the current study available from the corresponding author on reasonable request.

Abbreviations

CCDC:

Chinese Center for Disease Control and Prevention

CDC:

Centers for Disease Control and Prevention

CFR:

Case Fatality Rate

COVID-19:

Coronavirus Disease 2019

PCR:

Polymerase Chain Reaction

SPSS:

Statistical Package for Social Sciences

WHO:

World Health Organization

χ2 :

Chi-Square Test

95% CI:

Confidence Interval

References

  1. Bourouiba L. Fluid dynamics of respiratory infectious diseases. Annu Rev Biomed Eng. 2021;23(1):547–77. https://doi.org/10.1146/annurev-bioeng-111820-025044.

    Article  CAS  PubMed  Google Scholar 

  2. Stadnytskyi V, Bax CE, Bax A, Anfinrud P. The airborne lifetime of small speech droplets and their potential importance in SARS-CoV-2 transmission. Proceedings of the National Academy of Sciences. 2020; 117 (22): 11875–11877. Bibcode:2020PNAS.11711875S. https://doi.org/10.1073/pnas.2006874117.

  3. Centers for Disease Control and Prevention (CDC). Symptoms of Coronavirus. U.S. 22 February 2021. Archived from the original on 4 March 2021. https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html. Accessed January 4, 2024.

  4. Spiteri G, Fielding J, Diercke M, Campese C, et al. First cases of coronavirus disease 2019 (COVID-19) in the WHO European Region, 24 January to 21 February 2020. Euro Surveill. 2020;25(9):2000178. https://doi.org/10.2807/1560-7917.ES.2020.25.9.2000178.

    Article  PubMed  PubMed Central  Google Scholar 

  5. World Health Organization (WHO). Coronavirus disease (COVID-19) weekly epidemiological update and weekly operational update. November 24. 2023. https://covid19.who.int/region/emro/country/ye. Accessed January 4, 2024.

  6. World Health Organization (WHO). 14.9 million excess deaths associated with the COVID-19 pandemic in 2020 and 2021. Geneva: World Health Organization 2022. https://www.who.int/news/item/05-05-2022-14.9-million-excess-deaths-were-associated-with-the-covid-19-pandemic-in-2020-and-2021. Accessed January 4, 2024.

  7. Pijls BG, Jolani S, Atherley A, et al. Demographic risk factors for COVID-19 infection, severity, ICU admission and death: a meta-analysis of 59 studies. BMJ Open. 2021;11(1):e044640. https://doi.org/10.1136/bmjopen-2020-044640.

    Article  PubMed  Google Scholar 

  8. Castagnoli R, Votto M, Licari A, et al. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in children and adolescents: a systematic review. JAMA Pediatr. 2020;1(9):882–9. https://doi.org/10.1001/jamapediatrics.2020.1467.

    Article  Google Scholar 

  9. Chen F, Tian Y, Zhang L, et al. The role of children in household transmission of COVID-19: a systematic review and meta-analysis. Int J Infect Dis. 2022;11:122:266–675. https://doi.org/10.1016/j.ijid.2022.05.016.

    Article  CAS  Google Scholar 

  10. Baaees MO, Naiene JD, Al-Waleedi AA, et al. Community-based surveillance in internally displaced people’s camps and urban settings during a complex emergency in Yemen in 2020. Confl Health. 2021;15(1):54. https://doi.org/10.1186/s13031-021-00394-1. PMC 8256204. PMID 34225760.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Bin-Ghouth AS, Al-Shoteri S, Mahmoud N, Musani A, Baoom NA, Al-Waleedi AA, et al. SARS-CoV-2 Seroprevalence in Aden, Yemen: a population-based study. Int J Infect Dis. 2022;115:239–44. https://doi.org/10.1016/j.ijid.2021.12.330.

    Article  CAS  PubMed  Google Scholar 

  12. Alsabri M, Alhadheri A, Alsakkaf LM, et al. Conflict and COVID-19 in Yemen: beyond the humanitarian crisis. Global Health. 2021;17:83. https://doi.org/10.1186/s12992-021-00732-1.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Sallam TA, Al-Youssef M, A Bawazir A. Prevalence and classes of SARS-CoV-2 antibodies among COVID-19 suspected patients who attended a health care setting in Sana’a, Yemen. Asian J Immunol. 2021;5(3):41–8. https://doi.org/10.1186/s12879-023-08760-5.

    Article  CAS  Google Scholar 

  14. Taher WT, Bawazir AA, Sallam TA, et al. Seroprevalence and factors associated with SARS-CoV-2 infection among healthcare workers: cross-sectional study. BMC Infect Dis. 2023;23:761. https://doi.org/10.1186/s12879-023-08760-5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. OCHA. Humanitarian Data Exchange, Yemen: Humanitarian Needs Overview. https://data.humdata.org/dataset/yemen-humanitarian-needs-overview?.

  16. Chinese Center for Disease Control and Prevention (CCDC). The Novel Coronavirus Pneumonia Emergency Response Epidemiology Team. The epidemiological characteristics of an outbreak of 2019 Novel Coronavirus diseases (COVID-19) —China, 2020[J]. China CDC Wkly. 2020;2:113–22. https://doi.org/10.46234/ccdcw2020.032.

    Article  Google Scholar 

  17. Usman AB, Ayinde O, Akinyode A, Gbolahan A, Bello B. Epidemiology of coronavirus disease 2019 (COVD-19) outbreak cases in Oyo State South West Nigeria, March-April 2020. Pan Afr Med J. 2020;35(2):88. https://doi.org/10.11604/pamj.supp.2020.35.2.23832.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Centers for Disease Control and Prevention. (CDC) Provisional death counts for coronavirus disease 2019 (COVID-19): Weekly Updates by Select Demographic and Geographic Characteristics. Centers for Disease Control and Prevention, Atlanta, Georgia, United States. https://www.cdc.gov/nchs/nvss/vsrr/covid_weekly/index.htm. Retrieved on 09-01-2024.

  19. Africa Centres for Disease Control and Prevention (Africa CDC). Africa CDC Dashboard. Latest updates on the COVID-19 crisis from Africa CDC. https://africacdc.org/covid-19/ Accessed January 09, 2024.

  20. SetiadiW, Rozi IE, Safari D, Daningrat WOD, Johar E, Yohan B, et al. Prevalence and epidemiological characteristics of COVID-19 after one year of pandemic in Jakarta and neighbouring areas, Indonesia: a single center study. PLoS ONE. 2022;17(5):e0268241. https://doi.org/10.1371/journal.pone.0268241.

    Article  CAS  PubMed  Google Scholar 

  21. Djorwé S, Bousfiha A, Nzoyikorera N, Nkurunziza V, Ait Mouss K, Kawthar B, Malki A, Epidemiology. Clinical characteristics and risk factors of Coronavirus Disease 2019 (COVID-19) in Casablanca. Access Microbiol. 2023;5:000400. https://doi.org/10.1099/acmi.0.000400.

    Article  Google Scholar 

  22. Conti P, Younes A, Coronavirus. COV-19/SARS-CoV-2 affects women less than men: clinical response to viral infection. J Biol Regul Homeost Agents. 2020;34(2):339–43. https://doi.org/10.23812/Editorial-Conti-3.

    Article  CAS  PubMed  Google Scholar 

  23. Channappanavar R, Fett C, Mack M, et al. Sex-based differences in susceptibility to severe acute respiratory syndrome coronavirus infection. J Immunol. 2017;198(10):4046–53. https://doi.org/10.4049/jimmunol.1601896.

    Article  CAS  PubMed  Google Scholar 

  24. Nikolich-Zugich J, Knox KS, Rios CT, Natt B, Bhattacharya D, Fain MJ. SARS-CoV-2 and COVID-19 in older adults: what we may expect regarding pathogenesis, immune responses, and outcomes. Geroscience. 2020;42(2):505–14. https://doi.org/10.1007/s11357-020-00186-0.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Shah VK, Firmalm P, Alam A, Ganguly D, Chattopadhyay S. Overview of immune response during SARS-CoV-2 infection: Lessons from the past. Front. Immunol., 2020; 11(1949): https://doi.org/10.3389/fimmu.2020.01949.

  26. Chen N, Zhou M, Dong X, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020;395:507–13. https://doi.org/10.1016/S0140-6736(20)30211-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Gao L, Zheng C, Shi Q, Xiao K, Wang L, Liu Z, Li Z, Dong X. Evolving trend change during the COVID-19 pandemic. Front Public Health. 2022;10:957265. https://doi.org/10.3389/fpubh.2022.957265.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Boriani G, Guerra F, De Ponti R, et al. Five waves of COVID-19 pandemic in Italy: results of a national survey evaluating the impact on activities related to arrhythmias, pacing, and electrophysiology promoted by AIAC (Italian Association of Arrhythmology and Cardiac Pacing). Intern Emerg Med. 2023;18:137–49. https://doi.org/10.1007/s11739-022-03140-4.

    Article  PubMed  Google Scholar 

  29. Worldometer. Worldometer COVID-19 Data, Yemen. https://www.worldometers.info/coronavirus/country/yemen/ Accessed January 03, 2024.

  30. Wiemken TL, Khan F, Puzniak L, Yang W, et al. Seasonal trends in COVID-19 cases, hospitalizations, and mortality in the United States and Europe. Sci Rep. 2023;13(1):3886. https://doi.org/10.1038/s41598-023-31057-1.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Moriyama M, Hugentobler WJ, Iwasaki A. Seasonality of respiratory viral infections. Annu Rev Virol. 2020;7:83–101. https://doi.org/10.1146/annurev-virology-012420-022445.

    Article  CAS  PubMed  Google Scholar 

  32. Assessment Capacities Project (ACAPS). YEMEN COVID-19: Current situation and reasons for vaccine hesitancy Thematic Report. 10 January 2022. Available at; https://www.acaps.org/fileadmin/Data_Product/Main_media/20220110_acaps_yemen_analysis_hub_thematic_report_covid-19_and_vaccine_hesitancy_0.pdf.

  33. Biryukov J, Boydston JA, Dunning RA, et al. Increasing temperature and relative humidity accelerates inactivation of SARS-CoV-2 on surfaces. mSphere. 2020. https://doi.org/10.1128/msphere.00441-20.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Lai CC, Wang CY, Wang YH, et al. Hsueh. Global epidemiology of coronavirus disease 2019 (COVID-19): disease incidence, daily cumulative index, mortality, and their association with country healthcare resources and economic status. Int J Antimicrob Agents. 2020;55(4):105946. https://doi.org/10.1016/J.IJANTIMICAG.2020.105946.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. European Center for Disease Prevention and Control. (ECDC 2020) COVID-19 Situation Update Worldwide, as of November 9, 2020. https://www.ecdc.europa.eu/en/geographical-distribution-2019-ncov-cases. Retrieved on 08-11-2020.

  36. COVID-19 Australia. Epidemiology Report 75: reporting period ending 4 June 2023. Communicable diseases Intelligence. Australian Government Department Health Aged Care July. 2023;47:47: 1–21. https://doi.org/10.33321/cdi.2023.47.38.

    Article  Google Scholar 

  37. Vega-Alonso T, Lozano-Alonso JE, Ordax-Díez A. Comprehensive surveillance of acute respiratory infections during the COVID-19 pandemic: a methodological approach using sentinel networks, Castilla Y León, Spain, January 2020 to May 2022. Euro Surveillance/Eurosurveillance. 2023;28(21). https://doi.org/10.2807/1560-7917.es.2023.28.21.2200638.

  38. Wjst M, Wendtner C. High variability of COVID-19 case fatality rate in Germany. BMC Public Health. 2023;23(416). https://doi.org/10.1186/s12889-023-15112-0.

  39. Girma D, Dejene H, Adugna L, Tesema M, Awol M. COVID-19 Case Fatality rate and factors contributing to Mortality in Ethiopia: a systematic review of current evidence. Infect Drug Resist. 2022;15:3491–501. https://doi.org/10.2147/IDR.S369266.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Undurraga EA, Chowell G, Mizumoto K. COVID-19 case fatality risk by age and gender in a high testing setting in Latin America: Chile, March–August 2020. Infect Dis Poverty. 2021;10:11. https://doi.org/10.1186/s40249-020-00785-1.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Pijls BG, Jolani S, Atherley A, et al. Temporal trends of sex differences for COVID-19 infection, hospitalisation, severe disease, intensive care unit (ICU) admission and death: a meta-analysis of 229 studies covering over 10 M patients. F1000Res. 2022;115. https://doi.org/10.12688/f1000research.74645.1.

  42. Wu JM, McGoogan. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China. Summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention. JAMA. 2020;323:1239–42. https://doi.org/10.1001/jama.2020.2648.

    Article  CAS  PubMed  Google Scholar 

  43. Centers for Disease Control and Prevention (CDC). COVID-19 risks and information for older adults. Centers Disease Control Prev, 22 Feb. 2023, www.cdc.gov/aging/covid19/index.html.

Download references

Funding

There was no specific funding received for this work.

Author information

Authors and Affiliations

Authors

Contributions

Conceptualization, Edress W. and Al-Shehari W.; methodology, Khardesh A.; software, Alrahabi L.; validation, Edress W, Al-Shehari W. and Qais A.; formal analysis, Khardesh A.; data curation, Edress W.; writing—original draft preparation, Qais A, and Al-Shehari W.; writing—review and editing, Qais A.; supervision, Alrahabi L. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Wadhah Hassan Edrees.

Ethics declarations

Ethical approval

This study did not involve direct contact with humans. It is a retrospective study using the available data that was obtained from the Ministry of Health and Population. The Research and Ethics Committee of the Faculty of Applied Sciences at Hajjah University approved the ethical statement for conducting this study. In addition, permission to use the data in databases for research purposes was obtained from the Ministry of Health and Population. Furthermore, due to the retrospective nature of the study, the need for informed consent was waived by the Ministry of Health and Population.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it.The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Edrees, W.H., Abdullah, Q.Y., Al-Shehari, W.A. et al. COVID-19 pandemic in Taiz Governorate, Yemen, between 2020 and 2023. BMC Infect Dis 24, 739 (2024). https://doi.org/10.1186/s12879-024-09650-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12879-024-09650-0

Keywords