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. 2022 May 29;4:33–41. doi: 10.1016/j.ijregi.2022.05.010

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

Tejiokem Mathurin Cyrille 1,, Sadeuh-Mba Serge 2, Tchatchueng Mbougwa Jules Brice 1, Tagnouokam Ngoupo Paul Alain 2, Ngondi Grace 3, Fokam Joseph 4, Hamadou Achta 1, Nke Gisèle 5, Nwobegahay Julius 6, Tongo Marcel 7, Sander Melissa 8, Ndip Lucy 9, Perraut Ronald 10, Okomo Assoumou Marie Claire 11, Pefura Yone Eric Walter 12, Etoundi Mballa Georges Alain 13,14, Njouom Richard 2, Eyangoh Sara 13,15
PMCID: PMC9148624  PMID: 35720960

Abstract

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.

Keywords: First wave COVID-19, Cameroon, SARS-CoV-2 testing, early clinical features, pre-symptomatic, associated factors

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.

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.

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.

Acknowledgements

We thank all the study participants, the Ministry of Health's partners (The WHO country Office, The French Development Agency, The Foreign, Commonwealth & Development Office, US CDC, USAID, UNICEF and CHAI) and staff involved in the Cameroon COVID-19 Response to fight the global pandemic. We also thank the following persons from the laboratory network without whom the study would not have been possible: Njankouo Ripa, Messanga Landry, Kenmoe Sebastien, Monamele Glwadys, Ouapi Tiensi Diane, Fadimatou Bello Hamadou, Nemsi Daniel, Wouatedem Marguerite, Nguiala David, Masha Roland, Francis Yuya and Martial Yonga.

Contributor Information

Tejiokem Mathurin Cyrille, Email: tejiokem@pasteur-yaounde.org.

Sadeuh-Mba Serge, Email: sadeuhsergi@yahoo.fr.

Tchatchueng Mbougwa Jules Brice, Email: tchatchueng@pasteur-yaounde.org.

Tagnouokam Ngoupo Paul Alain, Email: tagnouokam@pasteur-yaounde.org.

Ngondi Grace, Email: ngondigrace@yahoo.fr.

Fokam Joseph, Email: josephfokam@gmail.com.

Hamadou Achta, Email: achta@hotmail.co.uk.

Nke Gisèle, Email: nkegisel@gmail.com.

Nwobegahay Julius, Email: nwobegahay@yahoo.com.

Tongo Marcel, Email: marcel.tongo@gmail.com.

Sander Melissa, Email: melissa.sander@gmail.com.

Ndip Lucy, Email: lndip@yahoo.com.

Perraut Ronald, Email: perraut@pasteur-yaounde.org.

Okomo Assoumou Marie Claire, Email: okomo2015@yahoo.fr.

Pefura Yone Eric Walter, Email: pefura2002@yahoo.fr.

Etoundi Mballa Georges Alain, Email: dretoundi@yahoo.fr.

Njouom Richard, Email: njouom@pasteur-yaounde.org.

Eyangoh Sara, Email: eyangoh@pasteur-yaounde.org.

References

  1. Abayomi A, Odukoya O, Osibogun A, Wright O, Adebayo B, Balogun M, et al. Presenting Symptoms and Predictors of Poor Outcomes Among 2,184 Patients with COVID-19 in Lagos State. Nigeria. Int J Infect Dis. 2021;102:226–232. doi: 10.1016/j.ijid.2020.10.024. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Abraha HE, Gessesse Z, Gebrecherkos T, Kebede Y, Weldegiargis AW, Tequare MH, et al. Clinical features and risk factors associated with morbidity and mortality among patients with COVID-19 in northern Ethiopia. International Journal of Infectious Diseases. 2021;105:776–783. doi: 10.1016/j.ijid.2021.03.037. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Abrahim SA, Tessema M, Defar A, Hussen A, Ejeta E, Demoz G, et al. Time to recovery and its predictors among adults hospitalised with COVID-19: A prospective cohort study in Ethiopia. PLoS One. 2020;15 doi: 10.1371/journal.pone.0244269. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Africa CDC. Africa Identifies First Case of Coronavirus Disease: Statement by the Director of Africa CDC. Africa CDC. 2020 https://africacdc.org/news-item/africa-identifies-first-case-of-coronavirus-disease-statement-by-the-director-of-africa-cdc/ (accessed February 18, 2022) [Google Scholar]
  5. Alkhouli M, Nanjundappa A, Annie F, Bates MC, Bhatt DL. Sex Differences in Case Fatality Rate of COVID-19: Insights From a Multinational Registry. Mayo Clin Proc. 2020;95:1613–1620. doi: 10.1016/j.mayocp.2020.05.014. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Almazeedi S, Al-Youha S, Jamal MH, Al-Haddad M, Al-Muhaini A, Al-Ghimlas F, et al. Characteristics, risk factors and outcomes among the first consecutive 1096 patients diagnosed with COVID-19 in Kuwait. EClinicalMedicine. 2020;24 doi: 10.1016/j.eclinm.2020.100448. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Byambasuren O, Cardona M, Bell K, Clark J, McLaws M-L, Glasziou P. Estimating the extent of asymptomatic COVID-19 and its potential for community transmission: Systematic review and meta-analysis. 2020 doi: 10.3138/jammi-2020-0030. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Chen C, Zhu C, Yan D, Liu H, Li D, Zhou Y, et al. The epidemiological and radiographical characteristics of asymptomatic infections with the novel coronavirus (COVID-19): A systematic review and meta-analysis. International Journal of Infectious Diseases. 2021;104:458–464. doi: 10.1016/j.ijid.2021.01.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Chen L, Li Q, Zheng D, Jiang H, Wei Y, Zou L, et al. Clinical Characteristics of Pregnant Women with Covid-19 in Wuhan, China. N Engl J Med. 2020;382:e100. doi: 10.1056/NEJMc2009226. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020;395:507–513. doi: 10.1016/S0140-6736(20)30211-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Chen T-M, Rui J, Wang Q-P, Zhao Z-Y, Cui J-A, Yin L. A mathematical model for simulating the phase-based transmissibility of a novel coronavirus. Infect Dis Poverty. 2020;9:24. doi: 10.1186/s40249-020-00640-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Dong Y, Mo X, Hu Y, Qi X, Jiang F, Jiang Z, et al. Epidemiology of COVID-19 Among Children in China. Pediatrics. 2020;145 doi: 10.1542/peds.2020-0702. [DOI] [PubMed] [Google Scholar]
  13. Elimian KO, Ochu CL, Ilori E, Oladejo J, Igumbor E, Steinhardt L, et al. Descriptive epidemiology of coronavirus disease 2019 in Nigeria, 27 February-6 June 2020. Epidemiol Infect. 2020;148:e208. doi: 10.1017/S095026882000206X. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Eyangoh S, Tchatchueng JB, Njouom R, Okomo Assoumou MC, Etoundi Mballa A. Scaling up laboratory testing for COVID-19 in Cameroon: Challenges, lessons learnt and perspectives. Lab Culture. 2021;25:22–25. [Google Scholar]
  15. Fernández-Rojas MA, Luna-Ruiz Esparza MA, Campos-Romero A, Calva-Espinosa DY, Moreno-Camacho JL, Langle-Martínez AP, et al. Epidemiology of COVID-19 in Mexico: Symptomatic profiles and presymptomatic people. Int J Infect Dis. 2021;104:572–579. doi: 10.1016/j.ijid.2020.12.086. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Fontanet A, Tondeur L, Grant R, Temmam S, Madec Y, Bigot T, et al. SARS-CoV-2 infection in schools in a northern French city: a retrospective serological cohort study in an area of high transmission. Euro Surveill. 2021;26 doi: 10.2807/1560-7917.ES.2021.26.15.2001695. France, January to April 2020. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Gandhi M, Yokoe DS, Havlir DV. Asymptomatic Transmission, the Achilles’ Heel of Current Strategies to Control Covid-19. N Engl J Med. 2020;382:2158–2160. doi: 10.1056/NEJMe2009758. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Götzinger F, Santiago-García B, Noguera-Julián A, Lanaspa M, Lancella L, Calò Carducci FI, et al. COVID-19 in children and adolescents in Europe: a multinational, multicentre cohort study. Lancet Child Adolesc Health. 2020;4:653–661. doi: 10.1016/S2352-4642(20)30177-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Grant MC, Geoghegan L, Arbyn M, Mohammed Z, McGuinness L, Clarke EL, et al. The prevalence of symptoms in 24,410 adults infected by the novel coronavirus (SARS-CoV-2; COVID-19): A systematic review and meta-analysis of 148 studies from 9 countries. PLoS One. 2020;15 doi: 10.1371/journal.pone.0234765. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Guan W, Ni Z, Yu Hu, Liang W, Ou C, He J, et al. Clinical Characteristics of Coronavirus Disease 2019 in China. New England Journal of Medicine. 2020;382:1708–1720. doi: 10.1056/NEJMoa2002032. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Kim H-J, Hwang H, Hong H, Yim J-J, Lee J. A systematic review and meta-analysis of regional risk factors for critical outcomes of COVID-19 during early phase of the pandemic. Sci Rep. 2021;11:9784. doi: 10.1038/s41598-021-89182-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Kragholm K, Andersen MP, Gerds TA, Butt JH, Østergaard L, Polcwiartek C, et al. Association between male sex and outcomes of Coronavirus Disease 2019 (Covid-19) – a Danish nationwide, register-based study. Clin Infect Dis. 2020:ciaa924. doi: 10.1093/cid/ciaa924. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Kronbichler A, Kresse D, Yoon S, Lee KH, Effenberger M, Shin JI. Asymptomatic patients as a source of COVID-19 infections: A systematic review and meta-analysis. Int J Infect Dis. 2020;98:180–186. doi: 10.1016/j.ijid.2020.06.052. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Lai C-C, Ko W-C, Lee P-I, Jean S-S, Hsueh P-R. Extra-respiratory manifestations of COVID-19. Int J Antimicrob Agents. 2020;56 doi: 10.1016/j.ijantimicag.2020.106024. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Lechien JR, Chiesa-Estomba CM, Place S, Van Laethem Y, Cabaraux P, Mat Q, et al. Clinical and epidemiological characteristics of 1420 European patients with mild-to-moderate coronavirus disease 2019. J Intern Med. 2020;288:335–344. doi: 10.1111/joim.13089. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Lee P-I, Hu Y-L, Chen P-Y, Huang Y-C, Hsueh P-R. Are children less susceptible to COVID-19? J Microbiol Immunol Infect. 2020;53:371–372. doi: 10.1016/j.jmii.2020.02.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Li Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, et al. Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia. N Engl J Med. 2020;382:1199–1207. doi: 10.1056/NEJMoa2001316. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Mantovani A, Rinaldi E, Zusi C, Beatrice G, Saccomani MD, Dalbeni A. Coronavirus disease 2019 (COVID-19) in children and/or adolescents: a meta-analysis. Pediatr Res. 2021;89:733–737. doi: 10.1038/s41390-020-1015-2. [DOI] [PubMed] [Google Scholar]
  29. Mao L, Jin H, Wang M, Hu Y, Chen S, He Q, et al. Neurologic Manifestations of Hospitalised Patients With Coronavirus Disease 2019 in Wuhan, China. JAMA Neurol. 2020;77:683–690. doi: 10.1001/jamaneurol.2020.1127. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Mizumoto K, Kagaya K, Zarebski A, Chowell G. Estimating the asymptomatic proportion of coronavirus disease 2019 (COVID-19) cases on board the Diamond Princess cruise ship, Yokohama, Japan, 2020. Euro Surveill. 2020;25 doi: 10.2807/1560-7917.ES.2020.25.10.2000180. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Moriarty LF. Public Health Responses to COVID-19 Outbreaks on Cruise Ships — Worldwide. MMWR Morb Mortal Wkly Rep. 2020;69 doi: 10.15585/mmwr.mm6912e3. February–March 2020. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Netland J, Meyerholz DK, Moore S, Cassell M, Perlman S. Severe acute respiratory syndrome coronavirus infection causes neuronal death in the absence of encephalitis in mice transgenic for human ACE2. J Virol. 2008;82:7264–7275. doi: 10.1128/JVI.00737-08. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Nikolai LA, Meyer CG, Kremsner PG, Velavan TP. Asymptomatic SARS Coronavirus 2 infection: Invisible yet invincible. Int J Infect Dis. 2020;100:112–116. doi: 10.1016/j.ijid.2020.08.076. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Olumade TJ, Uzairue LI. Clinical characteristics of 4499 COVID-19 patients in Africa: A meta-analysis. Journal of Medical Virology. 2021;93:3055–3061. doi: 10.1002/jmv.26848. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. OMS | Bureau régional pour l'Afrique. Situation reports on COVID-19 outbreak - Sitrep 32, 07 October 2020. OMS | Bureau régional pour l'Afrique 2020. https://www.afro.who.int/fr/node/13467 (accessed February 19, 2022).
  36. Parker A, Koegelenberg CFN, Moolla MS, Louw EH, Mowlana A, Nortjé A, et al. High HIV prevalence in an early cohort of hospital admissions with COVID-19 in Cape Town. South Africa. S Afr Med J. 2020;110:982–987. doi: 10.7196/SAMJ.2020.v110i10.15067. [DOI] [PubMed] [Google Scholar]
  37. Patel NA. Pediatric COVID-19: Systematic review of the literature. Am J Otolaryngol. 2020;41 doi: 10.1016/j.amjoto.2020.102573. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Poyiadji N, Shahin G, Noujaim D, Stone M, Patel S, Griffith B. COVID-19-associated Acute Hemorrhagic Necrotizing Encephalopathy: Imaging Features. Radiology. 2020;296:E119–E120. doi: 10.1148/radiol.2020201187. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Raba AA, Abobaker A, Elgenaidi IS, Daoud A. Novel coronavirus infection (COVID-19) in children younger than one year: A systematic review of symptoms, management and outcomes. Acta Paediatr. 2020;109:1948–1955. doi: 10.1111/apa.15422. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Rajapakse N, Dixit D. Human and novel coronavirus infections in children: a review. Paediatr Int Child Health. 2021;41:36–55. doi: 10.1080/20469047.2020.1781356. [DOI] [PubMed] [Google Scholar]
  41. Randremanana RV, Andriamandimby S-F, Rakotondramanga JM, Razanajatovo NH, Mangahasimbola RT, Randriambolamanantsoa TH, et al. The COVID-19 epidemic in Madagascar: clinical description and laboratory results of the first wave, march-september 2020. Influenza and Other Respiratory Viruses. 2021;15:457–468. doi: 10.1111/irv.12845. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Rice BL, Annapragada A, Baker RE, Bruijning M, Dotse-Gborgbortsi W, Mensah K, et al. Variation in SARS-CoV-2 outbreaks across sub-Saharan Africa. Nat Med. 2021;27:447–453. doi: 10.1038/s41591-021-01234-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Tabata S, Imai K, Kawano S, Ikeda M, Kodama T, Miyoshi K, et al. Clinical characteristics of COVID-19 in 104 people with SARS-CoV-2 infection on the Diamond Princess cruise ship: a retrospective analysis. Lancet Infect Dis. 2020;20:1043–1050. doi: 10.1016/S1473-3099(20)30482-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Tan W, Zhao X, Ma X, Wang W, Niu P, Xu W, et al. A Novel Coronavirus Genome Identified in a Cluster of Pneumonia Cases — Wuhan, China 2019−2020. China CDC Weekly. 2020 [PMC free article] [PubMed] [Google Scholar]
  45. Temmel AFP, Quint C, Schickinger-Fischer B, Klimek L, Stoller E, Hummel T. Characteristics of olfactory disorders in relation to major causes of olfactory loss. Arch Otolaryngol Head Neck Surg. 2002;128:635–641. doi: 10.1001/archotol.128.6.635. [DOI] [PubMed] [Google Scholar]
  46. Viner RM, Mytton OT, Bonell C, Melendez-Torres GJ, Ward J, Hudson L, et al. Susceptibility to SARS-CoV-2 Infection Among Children and Adolescents Compared With Adults: A Systematic Review and Meta-analysis. JAMA Pediatrics. 2021;175:143–156. doi: 10.1001/jamapediatrics.2020.4573. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. WHO. Weekly epidemiological update on COVID-19 - 15 February 2022. https://www.who.int/publications/m/item/weekly-epidemiological-update-on-covid-19—15-february-2022 (accessed February 19, 2022).
  48. WHO . World Health Organization; 2020. Laboratory testing for coronavirus disease (COVID-19) in suspected human cases: interim guidance; p. 2020. 19 March. [Google Scholar]
  49. Yang R, Gui X, Xiong Y. Comparison of Clinical Characteristics of Patients with Asymptomatic vs Symptomatic Coronavirus Disease 2019 in Wuhan, China. JAMA Netw Open. 2020;3 doi: 10.1001/jamanetworkopen.2020.10182. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Zhu N, Zhang D, Wang W, Li X, Yang B, Song J, et al. A Novel Coronavirus from Patients with Pneumonia in China, 2019. New England Journal of Medicine. 2020;382:727–733. doi: 10.1056/NEJMoa2001017. [DOI] [PMC free article] [PubMed] [Google Scholar]

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