The Distribution and Determinants of COVID-19 in Sudan, 2020/2021: Analysis of Surveillance Data

doi:10.21203/rs.3.rs-1399172/v2

Background: Since the first case of COVID-19 in Sudan was reported in March 2020, the Federal Ministry of Health adopted an active surveillance system to collect and analyze information from the isolation centers and public and private laboratories about all suspected and confirmed COVID-19 cases. This study used the surveillance data to better understand the distribution and determinants of COVID-19 in Sudan and to construct a threshold level beyond which the dramatic surge may occur.

Methods: Data of suspected and confirmed COVID-19 cases were extracted from the line list prepared by the Surveillance and Information Department at the Federal Ministry of Health after obtaining ethical approval from the National Ethics Committee. Data were cleaned, coded, and analyzed using SPSS version 21. Frequencies and proportions were used to describe data. A univariate logistic regression analysis was used to determine the association of variables with the positivity of COVID-19. Variables with p-values < 0.05 in the univariate logistic analyses were included in multivariable logistic regression to determine the adjusted odds ratios (ORs) and their 95% confidence interval (CI). A two-sided α of less than 0.05 (p < 0.05) was considered statistically significant.

Results: Out of 48,545 suspected cases, 27,453 were positive. Four waves were seen, with a distinct explosion point of around 200 cases observed nationwide. Khartoum reported the highest number of cases. Of those tested positive, 16,444 (59.9%) were male and 11,009 (40.1%) were female. The mean (SD) age of cases was 41.1 (19.0) years with 21.6% of cases above 60 years. 14,780 (53.8%) of cases were asymptomatic. Fever, cough, shortness of breath, and loss of smell and taste were reported in 32.7%, 26.4%, 19.1 and 4.5% of confirmed cases, respectively. A total of 1,793 confirmed cases died; the case fatality rate was 6.5%. A considerable proportion of infection was reported among health workers. A univariate logistic regression analysis revealed that being symptomatic is significantly associated with testing negative for COVID-19 (odds ratio < 1).

Conclusions: COVID-19 was widely spread in Sudan with more cases in Khartoum, the capital of Sudan. The country experienced four waves with an observable epidemic explosion point of around 200 positive cases per week nationwide. Around half of the patients were asymptomatic; however, fever, cough, and shortness of breath were the commonest symptoms. The CFR all through was 6.5%, with death having a strong association with age. Further studies are recommended to clarify the image, especially among health workers. The study also highlighted the need to improve the quality of surveillance data.

COVID-19

surveillance

distribution and determinants

explosion point

epidemic threshold

Sudan

Coronavirus disease (COVID-19) is an emerging infectious disease caused by the SARS-CoV-2 virus. The disease was declared as a pandemic by the World Health Organization (WHO) in March 2020¹. By the end of December 2021, the number of cases worldwide reached 281.8 million, of which 5.4 million died². The virus spreads mainly by close contact with patients through respiratory droplets³. The disease presents with a broad spectrum of clinical features ranging from fever and mild respiratory symptoms to more severe presentations such as respiratory distress⁴. The most observed symptoms are fever, cough, shortness of breath, and fatigability⁵. Many of those who contracted the disease also reported the loss of smell and taste⁶ Gastrointestinal symptoms were also reported⁷. Worldwide, the initially estimated case fatality rate (CFR) was up to 15%; then it decreased to reach 4% and even lower in some regions where it’s estimated to be 0.04%⁸. Concerning the age distribution of COVID-19, the disease has higher occurrence rates among young (0 -15 and 15 – 64 years old) individuals than other age groups, but the mortality is higher among the elderly^9,10.

The Federal Ministry of Health (FMOH) data in Sudan showed that the first case of COVID-19 was reported in March 2020, a traveler came from the United Arab Emirates, the first cases were all “imported cases”. The local transmission was reported by the first week of April 2020. By December 17, 2021, Sudan identified 45,112 confirmed cases with 3,252 deaths¹¹. Sudan has adopted the interventions recommended by the WHO since February 2020. Surveillance of diseases, as a cornerstone of these measures, was changed from a sentinel-based system with weekly reports from 1918 (28%) health facilities to cover all health facilities asking for an immediate reporting of any suspected case of COVID-19 and zero reporting by the end of the day if there are no suspected cases. These include 41 isolation centers and 57 laboratories (41 private and 16 public).

This study used data collected through the surveillance system and registered in the line list, to report the distribution and determinants of COVID-19 in Sudan. The study also tries to determine whether there is a point (specific number of cases or threshold) from which the possibility of explosion of cases is very likely. The findings may feed the ongoing control activities and foster a better understanding of the clinical presentations, trends, and factors affecting the outcome.

The context: Sudan is a large country with more than 42 million population distributed over 18 states and 189 districts. Health in the country is provided through over 6850 primary, secondary, and tertiary facilities. The health system in the country is a three-tier system (nation, states, and districts) with clear responsibilities for each. The Health Emergency and Epidemic Control Directorate at the national level works with states to detect any threat to public health through indicator-and event-based surveillance systems to initiate response as indicated by a risk assessment of the detected disease or event. The FMOH asks states to investigate any suspected COVID-19 case and record sociodemographic data, clinical data, results of lab tests including RT-PCR test, underlying medical conditions, outcomes, travel history, and recently added vaccination history. The FMOH compiles all data received from states into one-line list.

Data extraction and analysis: For this retrospective, descriptive study data was extracted from the records of patients (positive or negative RT-PCR) included in the line list of the Department of Surveillance and Information, FMOH covering the period from March 2020 to February 2021. For the epi-curves, the data period was extended to include all cases up to December 2021. The data was extracted, cleaned, coded, and entered using SPSS version 22. The mean [standard deviation (SD)], frequencies, and proportions were used to describe data. A univariate logistic regression analysis was used to determine the association of variables with the positivity of COVID-19. Variables with p-values < 0.05 in the univariate logistic analyses were included in multivariable logistic regression to determine the adjusted odds ratios (ORs) and their 95% confidence intervals (CIs). A two-sided α of less than 0.05 (p < 0.05) was considered statistically significant.

Ethical clearance and consent: The ethical approval for this review has been obtained from the National Ethics Committee of FMOH in Sudan (28/12/2020/ 1-12-20). Data used here was obtained from the Department of Surveillance and Information, after deleting the names of participants. So the study participant’s consent was not required as the study did not use identifiable data. The Data collected for this study will not be used for other purposes.

The total suspected cases tested for COVID-19 using the RT-PCR test from January 2020, to February 2021, were 48,545 (98%) cases; of them, 27,453 (56.5%) tested positive. Over 85% of positive cases were reported from Khartoum state (21,076/76.8%), Gezira State (1,962/7.1%), and Red Sea State (741/2.7%). Of those tested positive, 16,444 (59.9%) were male, and 11,009 (40.1%) were female. The mean (SD) age of cases was 41.1 (19.0) years; however, distribution according to age groups showed that 6,639 (25.6%) of patients were from 20 – 30 years, 7,885 (30.4%) were from 31-50 years and those who are above 60 years were 5,607 (21.6%). The majority of suspected and confirmed cases had no known history of contact with confirmed or suspected cases of COVID-19. A total of 612 suspected cases was detected among health workers (HWs), 383 (62.5%) of them were positive (Table 1).

Figure 1A shows a similar ratio of males and females in confirmed cases along the epidemic curve. A total of 1,793 confirmed cases died; the case fatality rate (CFR) was 6.5%. Death was more among male cases (1,257-70.1%) than females and the difference was highly significant (p-value = 0.0001). the states showed different CFRs in various age groups (Figure 1B).

While 12,673 (46.2%) of confirmed cases presented with symptoms or signs, 14,780 (53.8%) had no complaints, and this varied between age groups (Figure 1C). Table 2 shows that 32.2% of confirmed cases presented with fever, and 26.4% presented with cough. Among the confirmed cases, 19.1% presented with shortness of breath, 16.8% with a sore throat, and 16.7% with a headache. Loss of smelling and taste was reported by 1,238 confirmed cases (4.50%). Univariate analysis showed that infection with COVID-19 increased with an increase in age, being a male, having contact with a patient, symptomatic, and presented with symptoms such as fever, cough, shortness of breath, sore throat, and loss of smelling and taste (Table 3). However, multivariate analysis showed that symptoms status is the only factor associated with COVID-19 positivity with an adjusted OR =0.10; 95% CI: 0.06 - 0.18) (Table 3). This means, having symptoms is significantly associated with a lower risk of COVID-19.

Data collected from March 2020 to December 2021, showed that the country’s epi-curve peaked four times (epidemic waves). The first wave was in the 21^st week of the year 2020, the second was in week 48, the third was in week 12 of the year 2021, and the last was in week 47 in 2021. Death also followed the same waving pattern. A specific range of cases or threshold was observed in all four peaks, after which the epidemic shot dramatically (explosion point) towards the peak without being interrupted by any measure was noted. This range was between 200 - 250 confirmed cases for all cases in Sudan (Figure 2A). Disaggregation of data by states shows that this point differs from one state to another. Throughout the four epidemic waves, the range in Khartoum State falls between 200 – 250 cases (Figure 2B), and for Gezira State, it ranges between 20 – 30 cases (Figure 2C), and for Red Sea state is around 10 -20 cases (Figure 2C).

Table (1): RT-PCR testing status, sociodemographic characteristics, and contact status of suspected and confirmed COVID-19 cases.

	RT-PCR results
	Negative (%)	Positive (%)	Total (%)
RT-PCR result
Total suspected cases	-	-	49,493
Total tested	21,092 (43.4)	27,453 (56.6)	48,545 (100)
Age group (n = 46,166)
Below 20	2,493 (12.3)	2,385 (9.20)	4,878 (10.6)
21 – 30	6,232 (30.8)	6,639 (25.6)	12,871 (27.9)
31 – 40	3,749 (18.5)	4,462 (17.2)	8,211 (17.8)
41 – 50	2,650 (13.1)	3,423 (13.2)	6,073 (13.2)
51 – 60	2,166 (10.7)	3,415 (13.2)	5,581 (12.1)
Above 60	2,945 (14.6)	5,607 (21.6)	8,552 (18.5)
Gender (n = 48,400)
Female	9,361 (44.6)	10,997 (40.1)	20,358 (42.1)
Male	11,646 (55.4)	16,396 (59.9)	28,042 (57.9)
Occupation (n = 1651)
Not working	41 (7.40)	87 (7.90)	128 (7.80)
Students	58 (10.5)	145 (13.2)	203 (12.3)
Housewives	86 (15.5)	148 (13.5)	234 (14.2)
Paid workers	74 (13.3)	159 (14.5)	233 (14.1)
Free lancers	67 (12.1)	174 (15.9)	241 (14.6)
Health care workers	229 (41.3)	383 (34.9)	612 (37.1)
Contact Status (n = 27,476)
No or no known contact	9,615 (76.8)	12,311 (82.3)	21,926 (79.8)
Yes	2,901 (23.2)	2,649 (17.7)	5,550 (20.2)

Table 2: Common symptoms and signs as reported (n = 48,545)

	RT-PCR results
	Negative (%)	Positive (%)	Total (%)
Symptomatic
No	9821 (46.6)	14780 (53.8)	24601 (50.7)
Yes	11271 (53.4)	12673 (46.2)	23944 (49.3)
Fever
No	13462 (63.8)	18483 (67.3)	31945 (65.8)
Yes	7630 (36.2)	8970 (32.7)	16600 (34.2)
Cough
No	14970 (71.0)	20208 (73.6)	35178 (72.5)
Yes	6122 (29.0)	7245 (26.4)	13367 (27.5)
Shortness of Breath
No	16800 (79.7)	22206 (80.9)	39006 (80.4)
Yes	4292 (20.3)	5247 (19.1)	9539 (19.6)
Sore throat
No	16607 (78.7)	22835 (83.2)	39442 (81.2)
Yes	4485 (21.3)	4618 (16.8)	9103 (18.8)
Headache
No	16606 (78.7)	22878 (83.3)	39484 (81.3)
Yes	4486 (21.3)	4575 (16.7)	9061 (18.7)
Loss of Smell and Taste
No	20232 (95.9)	26215 (95.5)	46447 (95.7)
Yes	860 (4.10)	1238 (4.50)	2098 (4.30)

Table 3: Crude and adjusted ORs with 95% CI to determine factors associated with positivity of COVID-19 in Sudan

	Crude OR (95% CI)	P-value	Adjusted OR (95% CI)	P-value
Age Group in Years
< 20	1		1
21 – 30	0.50 (0.47 - 0.54)	0.001*	0.60 (0.31 - 1.15)	0.125
31 – 40	0.56 (0.53 - 0.59)	0.0001*	0.62 (0.29 - 1.32)	0.217
41 – 50	0.63 (0.59 - 0.67)	0.0001*	0.90 (0.42 - 1.97)	0.801
51 – 60	0.68 (0.63 - 0.73)	0.0001*	0.82 (0.38 - 1.79)	0.619
> 60	0.83 (0.77 - 0.89)	0.0001*	0.91 (0.42 - 2.00)	0.815

Male, Gender	1.20 (1.16 - 1.24)	0.0001*	0.84 (0.61 - 1.16)	0.293

Occupation
Not working	1		1
Health worker	0.79 (0.53 - 1.18)	0.250	1.15 (0.60 - 2.17)	0.678
Student	1.18 (0.73 - 1.90)	0.503	0.88 (0.42 - 1.84)	0.726
Paid worker	1.01 (0.64 - 1.61)	0.958	0.68 (0.36 - 1.28)	0.229
House wife	0.81 (0.51 - 1.28)	0.369	0.53 (0.28 - 1.01)	0.053
Free lancers	1.22 (0.77 - 1.95)	0.396	0.92 (0.50 - 1.69)	0.789

Contact Status	0.71 (0.67 - 0.76)	0.0001*	0.71 (0.49 - 1.04)	0.075

Symptomatic	0.75 (0.72 - 0.78)	0.0001*	0.10 (0.06 - 0.18)	0.0001*

Fever	0.86 (0.83 - 0.89)	0.0001*	1.26 (0.84 - 1.87)	0.263

Cough	0.88 (0.84 - 0.91)	0.0001*	1.21 (0.89 - 1.65)	0.226

Shortness of Breath	0.93 (0.88 - 0.97)	0.001*	0.88 (0.65 - 1.19)	0.394

Sore throat	0.75 (0.72 - 0.78)	0.0001*	1.16 (0.86 - 1.57)	0.331

Headache	0.74 (0.71 - 0.76)	0.0001*	1.11 (0.83 - 1.48)	0.492

Loss of Smell and/or Taste	1.11 (1.02 - 1.21)	0.02*	1.56 (0.94 - 2.58)	0.084

While many countries have been fighting against COVID-19 since its appearance in China, Sudan remained free of the disease until March 8, 2020. The trends gradually increased, and then markedly shot to report the maximum weekly reported cases of 1,560 in the epidemic week 20 of the year 2020. During the same period, the pandemic spread worldwide with the top affected countries being the United States, Spain, Italy, and the United Kingdom¹². Following that time, the rates of new cases remained over 1,000 cases per week for six weeks during July and August 2020. Since that time, reported cases decreased to only 23 by October 2020 (epidemic week 42). Sudan witnessed the second wave in the epidemic week 49 (December 2020), when 1,445 new cases were reported. The wave extended for more than ten weeks before rates started to lower down by February 2021 significantly. Later the country experienced the third and the fourth waves consecutively in April and November 2021 (Figure 2). The trend looks the same to other African countries where 40 (73%) countries had experienced or were experiencing their second wave of cases by the end of 2020¹³. Out of the 18 states in Sudan, Khartoum is the state with the highest prevalence, as 72.6% of the cases were reported there. This variation from other states could be due to different factors, including the testing capacity, access to testing facilities, better knowledge of the people, willingness to be tested, and population density. In addition, cases reported among travelers intended to travel through Khartoum airport, the biggest airport in the country, also further add to high reporting in Khartoum.

The majority of Sudanese patients were males (59.7%) and their ages were 40 years and above (48%). A possible explanation for this male predominance could be due to the hesitancy of women to have the test, or that men are known to work outdoor (e.g. in the markets) so they are more at risk to contract the infection, other factors might also have influenced this result, further evaluation is recommended. This goes in line with the finding from a meta-analysis of 13 studies where the disease was found to be more among males with the common age range being 37 to 62 years old¹⁴. By February 9, 2021 (where we took the data for analysis), the number of deaths worldwide was around 2 million¹⁵. In Sudan, there were 1,793 registered deaths due to COVID-19, with an overall CFR of 6.5%. This is a far lower rate compared with the firstly reported CFR at the start of the pandemic, as Sudan was among the countries with the highest CFR reaching up to 25%¹⁶. Compared to the neighboring countries, Ethiopia as an example, the CFR in the early pandemic was around 2%^17,18. In the initial two months of the outbreak in South Sudan, the CFR was 1.1%¹⁹. By looking at other countries’ data, it is clear that Sudan still has a higher rate, this could be due to factors like the limited capacity of the health system, especially for critical cases, or maybe due to stigma from the disease especially in the early outbreak stages as and not contacting the health authorities and seeking healthcare earlier. In other countries, the CFR was initially very high, reaching 15% in some studies, and in July 2020, its range was 0.1 – 14%^{7, 12}. Most of the deaths in Sudan were among males comprising 70.1% of all deaths, with the most affected age group being those above 60 years (50.3% of all deaths). While some authors reported that the risk of death among males is two times higher than that of females, particularly in older ages (50 – 69 years)²⁰. The finding of this study showed that 53.8% of the confirmed cases were asymptomatic. This finding is consistent with a meta-analysis where the asymptomatic proportion of COVID-19 cases ranged from 4% to 40%²¹. In some populations, this proportion reached up to 75%²². The rest of the cases were commonly presented with fever, cough, and shortness of breath, these findings were consistent with other studies with the same order⁵. However, other authors concluded that shortness of breath is a frequent symptom, followed by cough and fever²³. Loss of the sense of smell and taste in this study was reported by 4.5% of patients. The same was reported, especially in the early course of the disease, as concluded by Nehme et. al.⁶, and self-reported by patients in a retrospective study conducted early in the pandemic²⁴. Other symptoms experienced by Sudanese patients were sore throat and headache.

An interesting result from the multivariate analysis is that being symptomatic (having symptoms such as fever, cough, and shortness of breath) is significantly associated with not being a COVID-19 case (adjusted OR (0.10 (0.06 - 0.18)), P-value < 0.0001). Further research may be needed to confirm this finding and to exclude other possible explanations. Examples of possible explanations are that, so many people seek testing for travel purposes, and samples are taken from all contacts whether they have symptoms or not. That has led to an increased proportion of asymptomatic confirmed cases. Low viral load in the upper respiratory tract rather than false negativity of PCR could be also considered²⁵. Other possible factors include mutations of the virus escaping detection, quality of sampling and testing, and efficacy of RT-PCR kits²⁶. These findings draw attention to the fact that symptoms are unnecessary as a determinant of detecting COVID-19 cases, which needs to be considered when updating the case definition.

The data from March 2020 to December 2021 showed four epidemic waves. After careful analysis to understand the epidemic^’s behavior and to find clues to support the control efforts, an exact point (number of cases) was observed, after which the disease dramatically spikes (we name it as an explosion point). The explosion point varies from one state to another and seems to be around 200 confirmed cases per week nationwide. Although, the explosion points might be due to a true rise in cases due to accelerated transmission in the community beyond this specified number (200); it can be due to an increase in testing and reporting as a result of an increased number of investigated contacts, something which did not happen in Sudan. The finding may be a helpful clue to define an epidemic threshold for each state and as an indication for resource mobilization to keep the number of cases below this point nationwide. This is similar to previous efforts attempting to identify the period when the reproductive number (as a determinant of spread) is constant or changing²⁷, and the efforts to understand and explain the sudden jump and spikes of the confirmed cases across waves²⁸.

Out of 612 suspected cases among health workers (HWs) reported, 383 (62.5%) of them were found to be positive. HWs include doctors, nurses, other health care providers, and public health officers. HWs, especially nurses and physicians, are at high risk of contracting the diseases. This fact is well established even in countries with strong health systems like Qatar²⁹. Some studies reported rates of disease of more than 5% among healthcare workers³⁰. A total of 21,069 of the suspected cases registered with any information on their contact status. The incompleteness of the data is a major issue and limits the surveillance system to study risk factors and develop associations.

COVID-19 was widely spreading in Sudan during 2020/ 2021. Khartoum State reported the highest number of cases during the four waves of the epidemic. Males were more affected than females and the disease affected mainly the 40 – 60 years’ age group. About 53.8% of cases were asymptomatic. The most typical symptoms were fever, cough, and shortness of breath, with the symptomatic status significantly associated with not having the disease (OR < 1); a finding that needs further research. The overall case-fatality rate was 6.5%, with a significant association with increasing age. A specific number of cases was observed, beyond which the number of cases dramatically multiplied (exploded) to reach the peak. That may be of help to establish an epidemic threshold and to guide control efforts.

It is strongly recommended that another study has to be conducted for a deeper analysis to assess the risk of transmission in HWs and guide preventive measures. The study highlighted the need for improvement of the quality of the surveillance data, in terms of the collected data and the process of registration, and the completeness of the line-list variables.

Limitations

The main limitation of this study is the inadequacy of the surveillance data. The line-list lacks very Important individual characteristics that could have added much to the findings and used to assess risk factors for getting the infection, having severe disease, and death.

COVID-19	Corona Virus Disease 2019
CFR	Case Fatality Rate
CI	Confidence Interval
FMOH	Federal Ministry of Health
HWs	Health Workers
OR	Odds Ratio
RT-PCR	Real-Time Polymerase Chain Reaction
SD	Standard Deviation
SPSS	Statistical Package for Social Science
WHO	World Health Organization

Ethics approval

The ethical approval was obtained from the national research ethical committee at the Federal Ministry of Health.

Consent for publication

Not applicable

Competing interests

All authors declared they have no conflict of interest

Acknowledgment

We would love to show appreciation to the staff in the surveillance and information department in the Federal Ministry of Health for their kind cooperation and support in all the research steps. Thanks also go to the Director-General of the HEEC. Special thanks to Erama Alawad and Mawada Abouzeid, the national COVID-19 surveillance’s focal team, for their openness and dedication to supporting this research.

Funding

Not applicable

Availability of Data

The data is available at the surveillance and Information Directorate at Sudan Federal Ministry of Health.

Authors’ affiliation:

¹Surveillance and information Directorate, HEEC, FMOH, Sudan

²FETP candidate, Sudan FETP.

³Alfager College for Science and Technology, Khartoum, Sudan

⁴Health Emergency Epidemic Control, FMOH, Sudan

⁵Surveillance officer, WHO office, Sudan

⁶Public Health Centre, Khartoum, Sudan

⁷Freelancer Biostatistician, Public Health Center, Khartoum, Sudan.

⁸WHO/ EMRO, Egypt

⁹ GHD/ EMPHNET, Jordan.

¹⁰Faculty of Medicine, University of Khartoum, Sudan

Author Contributions:

AIA, EMM, ASO, AKI and MHI conceptualization of the idea and outline the theme to be discussed. MAA, OAM, HA, IMI, AHD, AMA, BAAM and SGE, approved the idea and contributed with additional inputs. SAM, AIA, OAM and EMM analyzed the data and wrote the draft. HB, ASO, IDE, FMM, TAM, MMO, BAAM, MH, MS, CL and BAG revised the draft and modified the layout, suggested additional points, and enriched the discussion. All authors reviewed the draft and the modified versions and approved the submitted version.

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The Distribution and Determinants of COVID-19 in Sudan, 2020/2021: Analysis of Surveillance Data

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Abstract

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Version 2