Clinical presentation of COVID-19 at the time of testing and factors associated with pre-symptomatic cases in Cameroon.

Objectives: To describe the clinical features at time of testing and explore factors associated with SARS-CoV-2 infection and pre-symptomatic cases in Cameroon.
Methods: Data was collected on people in Cameroon who participated in COVID-19 testing by real-time reverse transcriptase-polymerase chain reaction between 1 March and 5 October 2020. After descriptive analysis, multivariate logistic regression was used to identify factors associated with SARS-CoV-2 infection and pre-symptomatic cases.
Results: Of 85 206 test participants, 14 863 (17.4%) were infected with SARS-CoV-2. The median age for cases was 38.4 years (interquartile range 29.6-49.4); 6.1% were aged <19 years, and 6.3% were ≥65 years. Of these cases, 46.5% had at least one symptom/sign with a median time from illness onset to testing of 6 days (interquartile range 3-9). Cough (64.2%), headache (46.5%), fatigue/malaise (46.0%), shortness of breath (30.6%) and myalgia/arthralgia (25.6%) were the most commonly observed symptoms/signs. Pre-symptomatic SARS-CoV-2 infection was associated with age <50 years, being male and absence of comorbidities.
Conclusion: This study provides a comprehensive summary of the early clinical profile of SARS-CoV-2 infection during the first wave of COVID-19 in Cameroon, which was dominated by pre-symptomatic illness. These findings would be helpful for SARS-CoV-2 surveillance and control at a regional level.

Background

In December 2019, a cluster of pneumonia cases, subsequently confirmed to be caused by a novel enveloped RNA betacoronavirus named SARS-CoV-2, appeared in Wuhan, China (Tan et al., 2020; Zhu et al., 2020). On January 7, 2020, the World Health Organization (WHO) named this virus 2019 novel coronavirus (2019-nCoV), and on February 11, 2020, it named the associated illness COVID-19. COVID-19 rapidly spread to other parts of China and globally to many countries (Li et al., 2020); at the time of writing, COVID-19 has affected more than 409 million people worldwide and caused 5.8 million deaths (WHO, 2022). The first case in Africa was detected in Egypt on February 14, 2020 (Africa CDC, 2020) since when over 5 million cases have been identified and more than 89 000 deaths registered.

Countries have been affected differently by the COVID-19 pandemic, ranging from high incidence and outcome rates in Europe and America to low in Africa (Rice et al., 2021). Although the mechanism is not well known, this disparity is potentially linked to the hotter environment and younger populations in Africa (Rice et al., 2021). We hypothesised that this difference could also extend to the clinical presentation of COVID-19 cases. Numerous authors have synthesised the clinical characteristics of COVID-19 in America, Asia and Europe (L. Chen et al., 2020; N. Chen et al., 2020; Guan et al., 2020), indicating high variability with a typical presentation of fever and respiratory symptoms and unusual manifestations without respiratory symptoms (e.g., cutaneous, neurological, ocular, gustatory and olfactory, and gastrointestinal) (Lai et al., 2020) or asymptomatic. The asymptomatic group represents a large proportion of cases (Kronbichler et al., 2020) which is characterised by the same infectivity as symptomatic infections (T.-M. Chen et al., 2020) and can even lead to significant subclinical lung abnormalities in a short time (Kronbichler et al., 2020; Tabata et al., 2020). In many African countries, data on clinical characteristics of SARS-CoV-2 infection and associated risk factors remain sparse (Olumade and Uzairue, 2021). Here we describe the clinical features at diagnosis and further explore factors associated with SARS-CoV-2 infection and pre-symptomatic COVID-19 cases in Cameroon to better understand this novel disease and inform ongoing strategies and efforts to identify cases and manage and control the current pandemic.

Methods

Data source, setting, and study design

The first COVID-19 case in Cameroon was identified on March 5, 2020, by the Centre Pasteur du Cameroun (CPC), the only institution at that time performing testing by real-time reverse transcriptase-polymerase chain reaction (RT-PCR). Gradually, with the support of the Ministry of Health and partners, CPC designed a strategy to scale-up COVID-19 diagnosis, which has resulted in 18 functioning testing laboratories in Cameroon (Eyangoh et al., 2021). In addition, a secure online platform (PlaCARD) was adapted from District Health Information Software 2 (DHIS-2) by CPC to enter, centralise and manage the data of people tested for COVID-19. We retrieved anonymised data (sociodemographic, clinical and biological) from the PlaCARD database.

Study participants

We included in our analysis individuals of any age registered in the PlaCARD database whose nasopharyngeal swab specimen was tested for COVID-19 by RT-PCR between 1 March and 5 October, 2020. Cameroonians were initially tested based on case definitions adapted from WHO guidelines taking into account clinical manifestations, contact with a confirmed case and travel history. Testing was then extended to volunteers from the general population. Suspected COVID-19 patients who died in hospital and could be tested by RT-PCR were also included in this analysis. Participants without any clinical symptoms or signs at diagnosis were considered pre-symptomatic. Children and adolescents were defined as being <19 years old at the date of laboratory diagnosis.

Data collection

A brief questionnaire was administered to those tested for COVID-19 covering sociodemographic details, comorbidities and medications taken, travel history, and self-reported clinical signs and symptoms. A nasopharyngeal swab specimen was then collected from participants, placed into media and transported at 4°C to laboratories.

Laboratory diagnosis

The COVID-19 diagnosis was conducted by RT-PCR assay following WHO interim guidance and the test manufacturer's instructions (WHO, 2020). During the first wave of the epidemic, testing was complex and challenging, using different diagnosis kits depending on availability (including Sansure Biotech, Inc. Changsha, Hunan China; Da An Gene Co., Ltd. Sun Yat-sen University, Guangzhou, China; Xpert Xpress SARS-CoV- 2 cartridges, Cepheid, Sunnyvale, CA, USA; Abbott Real-Time SARS-CoV-2; TaqPath™ COVID-19 CE-IVD RT-PCR Kit, Thermofisher; LightMix® SarbecoV E-gene plus EAV control; TIB Biolmol, Berlin, Germany). Each new diagnostic kit and reagent lot required laboratory verification and determination of the appropriate cycle threshold (Ct-value) for the target genes (open reading frame 1a or 1b, spike protein, nucleocapsid protein, envelop or RNA-dependent RNA polymerase) as described elsewhere (WHO, 2020). When the Ct-values of the target genes were below or equal to the cut-off, the tested case was considered laboratory-confirmed.

Data management and analysis

Crosschecking and data cleaning were performed before analysis. If data were missing, requests for clarification were sent to data entry officers, who then checked the questionnaires. If the record did not include information on a particular clinical characteristic, it was assumed that the characteristic was not present.

Statistical analysis

Participants’ characteristics were described. Categorical variables were summarised as percentages and continuous variables expressed as medians and interquartile ranges (IQRs), as appropriate. Subgroup analysis was conducted for children and adolescents. For univariate comparisons, we used analysis of variance, Mann-Whitney U or Kruskal-Wallis tests, according to data distribution. Chi-square tests and Fisher's exact tests were used for categorical variables as appropriate. A multivariate logistic regression model was used to identify factors associated significantly and independently with each outcome (SARS-CoV-2 infection, pre-symptomatic SARS-CoV-2 infection). Potential predictors were identified a priori and during univariate analysis if associated with an outcome with a P-value of <0.25. For the final model, variables not associated with a P-value of <0.05 were removed only if the odds ratios for the remaining variables were unchanged, taking interactions into account. All statistical analysis were performed using STATA 12.1 (College Station, Texas 77845, USA).

Results

Sociodemographic characteristics of participants and diagnosis tests results

From 1 March to 5 October 2020, nasopharyngeal swabs collected from 85 206 participants from all regions of the country were tested as indicated in Table 1 . More than 78% of swabs came from the Centre and Littoral regions. The first COVID-19 case was detected on 5 March 2020 in Yaoundé, the capital city of Cameroon, located in the Centre region. Confirmed cases were subsequently notified in other regions; the North region, the last to be COVID-19-free, reported its first case on 24 April 2020, after 7 weeks of the epidemic in Cameroon (Figure 1 ).

Table 1

Covid-19 positivity rates and beginning of data collection according to region from 1st March to 5th October 2020 in Cameroon

	COVID-19
	Suspected cases		Confirmed cases		Data Collection
Regions	N=85 206	(%)*	n = 14 863	(17.4%)**	Started on	First case identified on
Adamawa	1 764	2.1	318	(18.0)	23/03	10/04
Centre	52 697	61.8	8 989	(17.1)	15/02	05/03
East	3 099	3.6	828	(26.7)	29/03	08/04
Far North	765	0.9	193	(25.2)	26/03	07/04
Littoral	14 028	16.5	2 035	(14.5)	04/03	17/03
North	931	1.1	163	(17.5)	24/03	24/04
North West	1 467	1.7	470	(32.0)	24/03	19/04
South	1 608	1.9	456	(28.4)	14/03	31/03
South West	3 127	3.7	734	(23.5)	24/03	26/03
West	5 720	6.7	677	(11.8)	08/03	17/03

*(Ni/N)**(ni/Ni) Ni: suspected cases tested per regions; N: total number of suspected cases; ni=number of positive cases per region

Figure 1

COVID-19 molecular tests conducted during the first wave of the epidemic, 1 March to 5 October 2020, Cameroon.

Of the 85 206 participants tested, 14 863 were confirmed as infected by SARS-CoV-2, giving an overall positivity rate of 17.4% (95% CI: 17.2−17.7), which significantly increased with participant age. The median age of those tested was 36.5 years (IQR 27.8−47.4), with the average age of laboratory-confirmed COVID-19-positive cases higher than unconfirmed ones at 38.4 years (IQR 29.6−49.4) versus 36.1 years (IQR 27.6−46.8) (P<0.001). The majority of COVID-19 cases belonged to the 30−49 age group (50.3%) and were more likely to be male (male to female ratio 1.4). Only 6.1% of COVID-19 cases were aged <19 years, while 6.3% were aged ≥65 years (Table 2 ). Among participants whose samples were collected and tested after death (n=529), the global positivity rate was 28.4% (n=150) (Figure 2 ), varying significantly according to the month of sample collection with an average positivity of 46% during the first 3 months (March to May), declining to 6% in June to September. The median age was 54.6 years (IQR: 39.6−66.9, n=92).

Table 2

Clinical characteristics of participants at time of testing for Covid-19, 1st March to 5th October 2020, Cameroon

		COVID-19 infection (PCR test)
Characteristics	All participants N=85 206	Positive (n=14 863)	Negative (n=70 343)
Period of diagnosis				<0.001
March	1 338 (1.6)	462 (3.1)	876 (1.3)
April	7 765 (9.1)	1 720 (11.6)	6 045 (8.6)
May	19 225 (22.6)	5 455 (36.7)	13 770 (19.6)
June	15 296 (18.0)	3 859 (26.0)	11 437 (16.3)
July	7 754 (9.1)	1 489 (10.0)	6 265 (8.9)
August	14 226 (16.7)	906 (6.1)	13 320 (18.9)
September	19 602 (23.0)	972 (6.5)	18 630 (26.5)
Age	63 156*	11 586	51 570
Median (IQR) - year	36.5 (27.8-47.4)	38.4 (29.6-49.4)	36.1 (27.6-46.8)	<0.001
Distribution – n/total (%)
0-18	5 580 (8.8)	703 (6.1)	4 877 (9.5)
19-29	13 763 (21.8)	2 284 (19.7)	11 479 (22.3)
30-49	30 934 (49.0)	5 823 (50.3)	25 111 (48.7)
50-64	10 025 (15.9)	2 049 (17.7)	7 976 (15.5)
≥65	2 854 (4.5)	727 (6.3)	2 127 (4.1)
Gender	84 796*	14 804	69 992	<0.001
Female	35 569 (42.0)	6.262 (42.3)	29 307 (41.9)
Male	49 227 (58.1)	8 542 (57.7)	40 685 (58.1)
Coexisting disorders - n (%)
Any	3 464 (4.1)	984 (6.6)	2 480 (3.5)	<0.001
Diabetes	1 092 (1.3)	369 (2.5)	723 (1.0)	<0.001
Chronic renal disease	232 (0.3)	70 (0.5)	162 (0.2)	<0.001
Cardiovascular	1 632 (1.9)	489 (3.3)	1 143 (1.6)	<0.001
Immunosuppression	373 (0.4)	91 (0.6)	282 (0.4)	<0.001
Asthma	812 (1.0)	184 (1.2)	628 (0.9)	<0.001
Drug history at sample collection - n (%)
Antiviral	775 (0.9)	250 (1.7)	525 (0.8)	<0.001
Antibiotics	5 465 (6.4)	2 183 (14.7)	3 282 (4.7)	<0.001
Antimalarial	5 655 (6.6)	2 439 (16.4)	3 216 (4.6)	<0.001
Antipyretic	6 996 (8.2)	2 864 (19.3)	4 132 (5.9)	<0.001
	Symptoms – n (%)
No	65 186 (76.5)	7 953 (53.5)	57 233 (81.4)	<0.001
Any	20 020 (23.5)	6 910 (46.5)	13 110 (18.6)

*The denominators of patients who were included in the analysis are provided if they differed from the overall numbers in the group

Figure 2

COVID-19 epidemic curve, 1 March to 5 October 2020, Cameroon.

Comparison of clinical characteristics between SARS-CoV-2 infected and uninfected study participants

Of the 85 206 study participants, 20 020 (23.5%) presented at least one symptom/sign at testing. The median time elapsed from illness onset to sample collection was 6 days (IQR 3–9), with no difference by test result. Participants with laboratory-confirmed COVID-19 appeared to be more symptomatic than unconfirmed ones: 46.5% (6 910 of 14 863) versus 18.7% (13 110 of 70 343) (P<0.001). The proportion of symptomatic COVID-19-positive participants remained quite stable during the first 4 months of the pandemic at an average of 54% (6262/11495, data not shown), significantly decreasing in July to September 2020 to 7.4%. Among symptomatic COVID-19-positive participants, cough was the most common symptom/sign, with a frequency of 64.2%, followed by headache (46.5%), fatigue/malaise (46.0%), shortness of breath (30.6%), and myalgia/arthralgia (25.6%) (Table 3 ). Fever was noted in only 636 (9.2%) participants. Gastrointestinal symptoms were reported by 17.0% of participants (including diarrhoea (11.1%), nausea and/or vomiting (7.3%), inappetence (0.8%), constipation (0.1%) and/or abdominal pain (0.9%)). No participant presented with only gastrointestinal symptoms. Other symptoms commonly reported were runny nose (18.9%), sore throat (18.5%), anosmia (8.3%), conjunctival congestion (5.4%), ageusia (4.6%), skin rash (3.4%) and chest pain (1.4%). All other symptoms (dizziness, lumbar pain, ear pain and sweat) were reported by <1% of participants. Loss or change of sense of smell (anosmia) and/or taste (ageusia) was significantly more common in COVID-19 positive participants (9.2% versus 3.7%, P<0.001) (Table 3).

Table 3

Symptoms presented by suspected Covid-19 cases at time of testing, 1stMarch to 5th October 2020, Cameroon

		COVID-19 infection
Symptoms	All participants (N=20 020)	Yes (n=6 910)	No (n = 13 110	p
Time from symptom onset to sample collection	*6 955	2 833	4 122
Median (IQR; days)	6 (3 - 9)	6 (3-9)	6 (3-10)	<0.001
Cough	11 008 (55.0)	4 436 (64.2)	6 572 (50.1)	<0.001
Headache	8 732 (43.6)	3 212 (46.5)	5 520 (42.11)	<0.001
Fatigue/malaise	7 790 (38.9)	3 178 (46.0)	4 612 (35.2)	<0.001
Shortness of breath	5 557 (27.8)	2 111 (30.6)	3 446 (26.3)	<0.001
Myalgia (muscles ache) or arthralgia	4 404 (22.0)	1 770 (25.6)	2 634 (20.1)	<0.001
Sore throat	3 768 (18.8)	1 279 (18.5)	2 489 (19.0)	<0.001
Rhinorrhoea (runny nose)	3 921 (19.6)	1 304 (18.9)	2 617 (20.0)	<0.001
Diarrhoea	1 951 (9.8)	770 (11.1)	1 181 (9.0)	<0.001
Fever at sample collection	1 447 (7.2)	636 (9.2)	811 (6.2)	<0.001
Fever at sample collection / use of antipyretic before diagnosis	6 820 (34.1)	2 991 (43.3)	3 829 (29.2)	<0.001
Nausea and vomiting	1 244 (6.2)	502 (7.3)	742 (5.7)	<0.001
Conjunctival congestion	987 (4.9)	370 (5.4)	617 (4.7)	<0.001
Ageusia and/or anosmia	1 127 (5.6)	637 (9.2)	490 (3.7)	<0.001
Anosmia (loss of smell)	982 (4.9)	572 (8.3)	410 (3.1)	0.001
Ageusia(loss of taste)	558 (2.8)	316 (4.6)	242 (1.9)	<0.001
Ear pain	163 (0.8)	58 (0.8)	105 (0.8)	<0.001
Other symptoms or signs
Skin rash	753 (3.8)	236 (3.4)	517 (3.9)	<0.001
Abdominal pain	262 (1.3)	64 (0.9)	198 (1.5)	0.5
Chest pain	284 (1.4)	81 (1.2)	203 (1.6)	0.4
Inappetence	105 (0.5)	55 (0.8)	50 (0.4)	<0.001
Dizziness	53 (0.3)	17 (0.3)	36 (0.3)	0.1
Constipation	17 (0.1)	5 (0.1)	12 (0.1)	0.4
Lombar pain	12 (0.1)	3 (0.04)	9 (0.1)	0.6
Sweat	10 (0.1)	5 (0.1)	5 (0.04)	0.3

If the suspected case's record did not include information on a clinical characteristic, it was assumed that the characteristic was not present.

*The denominators of patients who were included in the analysis are provided if they differed from the overall numbers in the group

In terms of past medical history and medication, participants with a confirmed positive test for COVID-19 had taken antimalarial and antibiotics more than unconfirmed ones (Table 2) and had significantly more coexisting disorders, 6.9%, (984 of 14 863) versus 3.5% (2480 of 70 343) (P<0.001). In addition, more were suffering from diabetes, cardiovascular and chronic renal diseases, immunosuppression and asthma.

Clinical characteristics of children and young adolescents

Of the 5 580 children/adolescents tested, 703 (12.6%) were positive for COVID-19 representing 6.1% (703 of 11 586) of the overall laboratory-confirmed cases with documented age (Table 2). The median age of children/adolescents infected with SARS-CoV-2 was 14.0 years (IQR 8.6−16.7), with 4% (29 of 703) aged <1 year; 51% were female. Asthma was the most frequent coexisting disorder in 1.1% of child/adolescent COVID-19-positive participants. More than two-thirds of children/adolescents infected with SARS-CoV-2 were pre-symptomatic at the time of testing. Cough (55.6%), headache (49.8%), fatigue/malaise (30.0%), runny nose (22.9%), and sore throat (19.3%) were the most commonly reported symptoms. Fever was reported in only 23 (10.3%) children/adolescents.

Factors associated with COVID-19 positive, pre-symptomatic participants

COVID-19 positivity was significantly and independently associated with the presence of any symptom/sign at testing (adjusted odds ratio (aOR) 3.37 [3.23−3.52]), any coexisting disease (aOR 1.1 [1.01−1.20]) and with age. Compared with children/adolescents aged <19 years, the risk of infection increased with age with aOR 1.26 (1.15−1.38), 1.45 (1.33−1.58), 1.56 (1.42−1.72) and 1.88 (1.66-2.12), respectively, for participants aged 20−29, 30−49, 50−64 and ≥65 years (Table 4 ).

Table 4

Characteristics associated to Covid-19 laboratory-confirmed cases, 1stMarch to 5th October 2020, Cameroon (univariate and multivariate analysis)

	Laboratory-confirmed Covid-19 cases (PCR test)
Characteristics	N=85 206	(n=14 863)	OR (95%CI)*	p	aOR (95%CI)*	p
Period of diagnosis**				<0.001
September	19 602	972 (5.0)	0.14 (0.13-0.15)
August	14 226	906 (6.4)	0.18 (0.17-0.20)
July	7 754	1 489 (19.2)	0.64 (0.61-0.69)
June	15 296	3 859 (25.2)	0.91 (0.87-0.96)
March/ April/May	28 328	7 637 (27.0)	1
Region***				<0.001
North West	1 467	470 (32.0)	1.36 (1.20-1.53)
AD/NO/FN	3 460	674 (19.5)	0.70 (0.56-0.63)
West	5 720	677 (11.8)	0.39 (0.35-0.43)
Centre	52 697	8989 (17.1)	0.59 (0.56-0.63)
Littoral	14 028	2035 (14.5)	0.49 (0.46-0.52)
SW/SU/ES	7 834	2018 (25.8)	1
Age	63 158*	11 586		<0.001		<0.001
≥65	2 854	727 (25.5)	2.37 (2.11-2.66)		1.88 (1.66-2.11)
50-64	10 025	2 049 (20.4)	1.78 (1.62-1.96)		1.56 (1.42-1.72)
30-49	30 934	5 823 (18.8)	1.61 (1.48-1.75)		1.45 (1.33-1.58)
19-29	13 763	2 284 (16.6)	1.38 (1.26-1.51)		1.26 (1.15-1.38)
0-18	5 580	703 (12.6)	1		1
Gender	84 796*	14 804		0.34
Female	35 569	6 262 (17.6)	1.02 (0.98-1.05)
Male	49 227	8 542 (17.4)	1
Coexisting disorders				<0.001		0.03
Any	3 464	984 (28.4)	1.94 (1.80-2.09)		1.1 (1.01-1.20)
No	81 742	13 879 (17.0)	1		1
Symptoms				<0.001		<0.001
Any	20 020	6 910 (34.5)	3.79 (3.65-3.94)		3.37 (3.23-3.52)
No	65 186	7 953 (12.2)	1		1

*The denominators of patients who were included in the analysis are provided if they differed from the overall numbers in the group

The following variables were not considered in multivariate analysis

**Period of diagnosis: initially, participants were tested based on case definitions taking into account clinical manifestations, contact with a confirmed case and travel history. Then, the diagnosis was extended to population-level volunteers (increase of the testing capacity over time).

***Region: during the first months of the COVID-19 pandemic, the only laboratory conducting diagnosis by PCR was the “Centre Pasteur du Cameroun” located in the Centre Region and there were a system of samples transfer from other regions

As presented in Table 5 , pre-symptomatic COVID-19-positive participants were associated with age <50 years, male sex, absence of a coexisting disorder and Ct>30 (indicating low SARS-CoV-2 viral load at testing) on univariate analysis. In addition, the sample collection region and period (month) were associated with COVID-19-positive pre-symptomatic participants. Apart from Ct, which was not included in the multivariate analysis because of missing data (50%; 7426 of 14 863), all the above-listed variables remained significantly and independently associated with pre-symptomatic laboratory-confirmed COVID-19 positive cases.

Table 5

Characteristics associated to pre-symptomatic Covid-19 cases, 1stMarch to 5thOctober 2020, Cameroon (univariate and multivariate analysis)

	Pre-symptomatic Covid-19 cases
	N=14 863	n (%)	OR (95%CI)*	p	aOR (95%CI)*	p
Age group (years, n=11 610)				<0.001		<0.001
<19	704	483 (68.6)	2.71 (2.19 – 3.37)		2.38 (1.86 – 3.00)
19 - 29	2 282	1 309 (57.4)	1.67 (1.41 – 1.98)		1.51 (1.25 – 1.83)
30 - 49	5 835	3 223 (55.2)	1.53 (1.31 – 1.79)		1.54 (1.29 – 1.84)
50 - 64	2 058	993 (48.2)	1.16 (0.98 – 1.37)		1.19 (0.98 – 1.44)
≥ 65	731	326 (44.6)	1		1
Gender (n=14 829)				0.007		<0.001
Male	8 549	4 650 (54.4)	1.09 (1.02 – 1.17)		1.23 (1.13 – 1.33)
Female	6 280	3 276 (52.2)	1		1
Presence of any co-morbidity				<0.001		<0.001
No	13 899	7 739 (55.7)	4.37 (3.75 – 5.10)		3.19 (2.67 – 3.81)
Yes	989	221 (22.4)	1		1
Period of diagnosis				<0.001		<0.001
September	972	899 (92.5)	18.00 (14.11 – 22.95)		13.24 (10.11 – 17.32)
August	906	767 (84.7)	8.06 (6.69 – 9.72)		6.39 (5.13 – 7.95)
July	1 490	1 054 (70.7)	3.53 (3.13 – 3.99)		2.98 (2.57 – 3.45)
June	3 867	2 131 (55.1)	1.79 (1.66 – 1.94)		1.67 (1.52 – 1.83)
March/ April/May	7 653	3 109 (40.6)	1		1
Region				<0.001		<0.001
North West	470	409 (87.0)	11.39 (8.57 – 15.12)		9.47 (7.01 – 12.79)
AD/NO/FN	674	509 (75.5)	5.24 (4.30 – 6.38)		3.21 (2.53 – 4.07)
West	666	474 (71.2)	4.19 (3.47 – 5.07)		3.76 (3.04 – 4.64)
Centre	9 019	5 009 (55.5)	2.12 (1.92 – 2.34)		1.93 (1.72 – 2.19)
Littoral	2 038	810 (39.7)	1.12 (0.99 – 1.27)		0.95 (0.78 – 1.15)
SW/SU/ES	2 021	749 (37.1)	1		1
Cycle Threshold**(CT, n=7437)				<0.001
>=30	3 300	505 (41.3)	1.49 (1.30 – 1.70)
20-29	2 915	1 219 (41.8)	1.02 (0.89 – 1.17)
<20	1 222	1 689 (51.2)	1

*95%CI: Confidence interval; AD/NO/FN: Adamawa/North/Far North; SW/SU/ES: South West/South/East

**Cycle Threshold was not considered in further analysis because of high level of missing values (50%)

Discussion

To our knowledge, our study is one of the first detailed reports of COVID-19 clinical characteristics in Cameroon using data from the first wave of the pandemic on a relatively representative population. Data analysed came from all 10 regions of the country and were collected at the time of testing to describe the early clinical presentation of SARS-CoV-2 infected participants. A total of 14 863 SARS-CoV-2 infected cases were considered in our analysis, representing 71% of the 20 924 cases notified by the country from 1 March to 5 October 2020 (the period of our study) (OMS | Bureau régional pour l'Afrique, 2020).

In this study, SARS-CoV-2 infected cases were observed in all age groups, and the positivity rate increased with age. One of every two SARS-CoV-2-infected participants belonged to the 30−49 years age group, and 58% were men. This finding is consistent with previous data from the WHO African region indicating that, among cases with documented age and sex, men were more affected than women in the predominant 30−49 age group (OMS | Bureau régional pour l'Afrique, 2020). This may be related to the age structure of the population in Cameroon, and in Africa, compared with other continents. Other epidemiological studies in and outside Africa reported higher rates of COVID-19 in men than women (Elimian et al., 2020; Kim et al., 2021; Olumade and Uzairue, 2021; Randremanana et al., 2021). Male sex has been shown to be an independent risk factor for a severe course of COVID-19 in many studies (Alkhouli et al., 2020; Kragholm et al., 2020). Although the mechanism underlying this difference has not been elucidated, female sex hormones and X-linked genes have been suggested to be protective.

Children and adolescents aged <19 years accounted for 6.1% of total SARS-CoV-2 infected participants in our analysis, higher than the 1%−2% of COVID-19 cases described worldwide and the 2% reported in China and 1.7% in North America (Dong et al., 2020; Viner et al., 2021). In Africa, the reported proportion of children and young people with COVID-19 ranges from 5.8% to 11.7% (Abayomi et al., 2021; Abraha et al., 2021; Elimian et al., 2020; Randremanana et al., 2021). Unlike other respiratory viruses, children and adolescents appear less susceptible to this infection than adults. A tentative explanation for this could be the immaturity of their immune system and the absence of the angiotensin-converting enzyme 2 (ACE) cellular receptor that helps SARS-CoV-2 enter cells (Lee et al., 2020; Viner et al., 2021). The complexity of sampling for testing and the fact that children/adolescents were at home after the closure of schools during the government's COVID-19 restriction measures resulted in a lower number tested.

SARS-CoV-2-infected participants had significantly more coexisting disorders than uninfected ones, suggesting they might have been at higher risk for infection. This situation is possibly the consequence of weaknesses of their immune system or the presence of ACE (Patel, 2020; Raba et al., 2020; Rajapakse and Dixit, 2021). Symptoms/signs reported by COVID-19-positive participants were diverse and their frequencies variable indicating the involvement of multiple organs and suggesting a difference in viral tropism (Guan et al., 2020). Among the 6 910 COVID-19-positive symptomatic participants in this study, cough (64.2%), headache (46.5%), fatigue/malaise (46.0%), shortness of breath (30.6%) and myalgia/arthralgia (25.6%) were the most common symptoms/sign. In children/adolescents aged <19 years, the most common signs/symptoms were cough (55.6%), headache (49.8%), fatigue/malaise (30.0%), runny nose (22.9%) and sore throat (19.3%).

Our findings on the sequence and frequency of symptoms/signs differed from those found in other studies in Africa. In Lagos State, Nigerian authors reported cough (19.3%), fever (13.7%), difficulty in breathing (10.9%), headaches (7.3%) and weakness (6.3%) as the most common symptoms among 906 COVID-19 symptomatic patients (Abayomi et al., 2021). A study in Northern Ethiopia reported cough (50.6%), myalgia (31.1%), headache (28.7%), fever (23.6%) and dyspnoea (16.3%) among 682 symptomatic COVID-19 patients (Abraha et al., 2021). Authors from Malagasy observed cough (27.2%), fever (18.7%), weakness (14.7%), runny nose (13.3%) and headache (13.1%) as the most common symptoms among 2 242 SARS-CoV-2 cases (Randremanana et al., 2021). A systematic review of literature from Africa, which included 4 499 COVID-19 patients, found fever (42.8%), cough (33.3%), headache (11.3%), breathing problems (16.8%) and rhinorrhea (9.4%) to be the most common symptoms (Olumade and Uzairue, 2021). In the above studies, fever was frequently reported, while its frequency in our study was low at 9.2%. However, if we consider participants who had taken antipyretic drugs and reported not having had fever before testing, the level increases to 43.3% (Table 3), similar to that reported in other African countries. An observational study conducted in Europe including 1 420 mild or moderate COVID-19 patients indicated headache (70.3%), loss of smell (70.2%), nasal obstruction (67.8%), cough (63.2%), asthenia (63.3%), myalgia (62.5%), rhinorrhea (60.1%), gustatory dysfunction (54.2%) and sore throat (52.9%) as the most common symptoms. Fever was also reported at 45.4% in that study (Lechien et al., 2020). In a cohort of 582 paediatric cases of SARS-CoV-2 infection from 21 European countries, signs and symptoms at presentation at health care institutions included pyrexia (65%), upper respiratory tract infection (54%), headache (28%), lower respiratory tract infection (25%) and gastrointestinal symptoms (22%) (Götzinger et al., 2020; Mantovani et al., 2021; Patel, 2020; Raba et al., 2020; Rajapakse and Dixit, 2021). In a study conducted in Mexico which included 196 738 confirmed COVID-19 cases, the main symptoms identified were headache (50%), myalgia/arthralgia (38%), sore throat (36%), dry cough (23%) and runny nose (19%) (Fernández-Rojas et al., 2021). A systematic review and meta-analysis, including studies from 9 countries (24 410 adults with confirmed COVID-19, the majority from China), indicated that the most prevalent symptoms were fever (78%), cough (57%), fatigue (31%), hyposmia (25%) and dyspnoea (23%) (Grant et al., 2020).

One notable finding is related to the low frequency of taste and olfactory disorders which was observed in our study and similarly reported by other studies conducted in Africa during the first wave of the pandemic with frequencies varying from 3% to 11% (Abayomi et al., 2021; Abraha et al., 2021; Parker et al., 2020; Randremanana et al., 2021). This low incidence could be related to inadequate collection methods based on participant declaration without clear definitions of the characteristics of the disorders nor specific chemosensory testing. In addition, our study concerned the early description of signs and symptoms, which could further explain the low frequency of taste and olfactory disorders. Nevertheless, we recognise that taste and olfactory dysfunction emerged as a frequent manifestation of COVID-19 with related recommendations published during the pandemic. The relationship between COVID-19 and taste or smell disorders needs further research, as these are also described after other viral respiratory infections. Animal models suggest that coronaviruses might track into the brain via the olfactory nerve or bulb or both and cause neuronal damage or death (Mao et al., 2020; Netland et al., 2008; Poyiadji et al., 2020; Temmel et al., 2002).

Among participants without confirmed SARS-CoV-2 infection, the presence of symptoms is an indication that other respiratory viruses were circulating in the community at the same time. However, we have not determined if sampling conditions (collection, transport and storage) produced SARS-CoV-2 false negatives or if other pathogens were involved (Fontanet et al., 2021).

We observed that 53.5% of our study participants with confirmed SARS-CoV-2 infection were pre-symptomatic at the time of testing. Similar proportions of COVID-19 cases without clinical symptoms/signs at time of diagnosis were reported in other studies conducted in Nigeria (58.3% to 66.3%), Uganda (45%) and Madagascar (56.6%); a study conducted in Northern Ethiopia reported an even higher proportion (74.0%) (Abraha et al., 2021; Abrahim et al., 2020; Byambasuren et al., 2020; Yang et al., 2020). Several studies conducted in the Middle East, Europe, Asia and the United States also showed similar proportions ranging from 45% to 58% (Almazeedi et al., 2020; Mizumoto et al., 2020; Moriarty, 2020; Gandhi et al., 2020). Conversely, other studies have reported a low proportion (13%) of COVID-19 cases without clinical symptoms/signs (Chen et al., 2021; Fernández-Rojas et al., 2021). These observations suggest considerable uncertainty in determining the true proportion of asymptomatic SARS-CoV-2 infection. There is a need to consider the follow-up period to distinguish between asymptomatic and pre-symptomatic cases (Gandhi et al., 2020; Nikolai et al., 2020). In a study conducted in Ethiopia, it was reported that 18% of asymptomatic individuals progressed to symptomatic later.

In our study, participants aged <50 years, male and without coexisting disorders were significantly and independently associated with pre-symptomatic SARS-CoV-2-infected participants. Young age and absence of coexisting disorders could reflect good immunity or the absence of ACE. However, the mechanism underlying the association of male sex with asymptomatic SARS-CoV-2 infection is not clear, particularly as male sex might be associated with severe outcome (Alkhouli et al., 2020).

Our study has several strengths. It is one of the first analyses of almost nationwide data concerning clinical characteristics of people tested early by RT-PCR for COVID-19. The large number of confirmed SARS-CoV-2 cases and the inclusion of unconfirmed cases enabled us to conduct detailed analyses despite some missing data. The study also has some limitations. Symptoms were self-reported and may be subject to recall bias or reluctance to report since COVID-19 was very stigmatising in the tested population at the time. In the follow-up of laboratory-confirmed cases, it would have been interesting to identify those who were asymptomatic at the time of testing who subsequently become symptomatic, allowing us to estimate the “true” proportion of asymptomatic cases. The evolving nature of the SARS-CoV-2 pandemic, including the advent of the Delta and Omicron variants which has completely changed the clinical presentation of patients and patterns of transmission including in Africa, and the fact that most African countries are now suffering from the third or fourth wave of the pandemic, mean our data are now out-dated. Despite these limitations, our results constitute baseline data for future comparisons across different waves of COVID-19.

In conclusion, our study provides substantial data on the clinical profile of SARS-CoV-2 infection at the time of testing, dominated by pre-symptomatic cases during the first wave of the pandemic in Cameroon. Symptoms/signs were diverse and inconsistent in frequency as observed in other settings within and outside of Africa. Male participants without coexisting morbidities and of a young age were likely to be pre-symptomatic. Overall, these findings would be very helpful for health authorities to evaluate and optimise the ongoing strategies for SARS-CoV-2 surveillance and control at regional levels.

Ethics

Approval was obtained from the Cameroon National Ethics Committee for Research in Human Health (N°2020/05/1231/CE/CNERSH/SP) to conduct this analysis on de-identified surveillance data in light of the urgent need to share findings within the ongoing response to a public health emergency of international concern.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors.