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. 2024 Aug 5;4(8):e0003550. doi: 10.1371/journal.pgph.0003550

Mild and moderate COVID-19 during Alpha, Delta and Omicron pandemic waves in urban Maputo, Mozambique, December 2020-March 2022: A population-based surveillance study

Brecht Ingelbeen 1,2,*,#, Victória Cumbane 3,#, Ferão Mandlate 3, Barbara Barbé 1, Sheila Mercedes Nhachungue 3, Nilzio Cavele 3, Cremildo Manhica 3, Catildo Cubai 3, Neusa Maimuna Carlos Nguenha 3, Audrey Lacroix 4, Joachim Mariën 1, Anja de Weggheleire 5, Esther van Kleef 1,2, Philippe Selhorst 1, Marianne A B van der Sande 1,2, Martine Peeters 4, Marc-Alain Widdowson 1, Nalia Ismael 3,‡, Ivalda Macicame 3,‡
Editor: Nei-yuan Hsiao6
PMCID: PMC11299809  PMID: 39102391

Abstract

In sub-Saharan Africa, reported COVID-19 numbers have been lower than anticipated, even when considering populations’ younger age. The extent to which risk factors, established in industrialised countries, impact the risk of infection and of disease in populations in sub-Saharan Africa, remains unclear. We estimated the incidence of mild and moderate COVID-19 in urban Mozambique and analysed factors associated with infection and disease in a population-based surveillance study. During December 2020-March 2022, 1,561 households (6,049 participants, median 21 years, 54.8% female, 7.3% disclosed HIV positive) of Polana Caniço, Maputo, Mozambique, were visited biweekly to report respiratory symptoms, anosmia, or ageusia, and self-administer a nasal swab for SARS-CoV-2 testing. Every three months, dried blood spots of a subset of participants (1,412) were collected for detection of antibodies against SARS-CoV-2 spike glycoprotein and nucleocapsid protein. Per 1000 person-years, 364.5 (95%CI 352.8–376.1) respiratory illness episodes were reported, of which 72.2 (95%CI 60.6–83.9) were COVID-19. SARS-CoV-2 seroprevalence rose from 4.8% (95%CI 1.1–8.6%) in December 2020 to 34.7% (95%CI 20.2–49.3%) in June 2021, when 3.0% were vaccinated. Increasing age, chronic lung disease, hypertension, and overweight increased risk of COVID-19. Older age increased the risk of SARS-CoV-2 seroconversion. We observed no association between socio-economic status, behaviour and COVID-19 or SARS-CoV-2 seroconversion. Active surveillance in an urban population confirmed frequent COVID-19 underreporting, yet indicated that the large majority of cases were mild and non-febrile. In contrast to reports from industrialised countries, social deprivation did not increase the risk of infection nor disease.

Introduction

In sub-Saharan Africa, reported COVID-19 cases and deaths were lower than expected from estimated SARS-CoV-2 seroprevalence in the region, and age-specific infection fatality [1,2]. Older age, deprivation, black ethnicity (compared to white) and co-morbidities have been found to independently increase the risk of COVID-19 disease or death in different contexts [3–5]. Younger age groups less frequently manifested symptoms or were hospitalised when infected, but also had lower infection rates [6,7]. HIV increased the risk of COVID-19-related death [8], as did comorbidities as hypertension, diabetes, or chronic kidney of pulmonary disease [3]. Higher COVID-19 incidence among deprived populations has been hypothesised to result from inequalities in the ability to work remotely, and by higher secondary infection rates within (more crowded) households [9].

The extent to which non-pharmaceutical interventions had an impact on COVID-19 incidence in sub-Saharan African settings is still poorly understood. Other studies in Eastern Africa have shown a reduction in excess mortality among children, indicating an effect of social restrictions on pathogen spread [10].

In Mozambique (estimated pop. 2020 31.2 million), 184,219 COVID-19 cases and 2010 deaths were reported during 2020–21, yet excess deaths due to the pandemic have been estimated at 78,100 (95%CI 54,100–109,000) [11]. The excess mortality rate (139 per 100,000, 95%CI 96–194) was comparable to the global all-age estimate (120 per 100,000, 95%CI 113–129). COVID-19 vaccination started on 7 March 2021. By 8 September 2021, 5.0% of the Mozambican population had received at least one dose of vaccine; by 8 March 2022, 40.2% had.

In Maputo City (estimated pop. 2020 1.1 million), the capital of Mozambique, in 2020–21, COVID-19 testing was centralised in two COVID-19 management facilities, but mild/moderate cases were unlikely to go there. Here, we provide a comprehensive description of the clinical range of mild and moderate COVID-19 in urban Maputo. We then estimate SARS-CoV-2 (infection) seroprevalence, COVID-19 (disease) incidence rates, and analyse demographics, comorbidities, and exposures increasing the risk of SARS-CoV-2 seroconversion and of COVID-19.

Methods

Study design and population

Between 15 December 2020 and 31 March 2022, population based surveillance in urban Maputo consisted of two components: biweekly follow-up of households to record possible COVID-19 cases and three-monthly sero-surveys to track SARS-CoV-2 antibodies in a subset of participants. Recruited households were embedded in the Health and Demographic Surveillance System (HDSS) of Polana Caniço, covering 15,393 residents.

Sampling strategy

Study interviewers were each assigned a housing block for which they received a list of households enrolled in the HDSS. Eligible households were recruited consecutively following informed consent by the household head and by individual household members randomly selected for the repeated sero-survey. To participate in the study, household members had to be residing in the household since ≥3 months, including all ages. Subsequently, households were visited or phoned every two weeks during one year to detect possible COVID-19 cases at the time of the visit or with symptom onset in the two weeks prior to the visit. Household enrolment stopped after three months. After that, biweekly follow-up visits continued for a year and the second sero-survey round started.

Data collection

At baseline, household-level water- and sanitation conditions, individual weight and height (measured during a visit to determine Body Mass Index, BMI, in ≥16 year olds), self-reported comorbidities, smoking, and behaviour potentially determining exposure risk (e.g., use of public transportation, healthcare occupation, crowding) were recorded in electronic questionnaires. Within the HDSS, participating household members’ demographics, educational level, and households’ socio-economic quintile (relative to wealth across HDSS households) were previously recorded and last updated in 2019. During the biweekly household follow-up visits, possible COVID-19 cases in the household were registered, recording clinical signs and symptoms, potential exposures (according to the World Health Organization’s Revised case report form for Confirmed Novel Coronavirus COVID-19, accessed on 4 June 2020), and prior COVID-19 vaccination. A possible COVID-19 case was any respiratory sign or loss of smell or taste, anosmia, or ageusia, with or without fever, and symptom onset in the previous two weeks, among any household member. Possible COVID-19 cases were asked to self-administer a nasal swab for SARS-CoV-2 PCR testing, either–if present–during the household visit, or–if absent–during an ad hoc interviewer visit scheduled shortly after. Household contacts of possible cases were not tested. If COVID-19 was confirmed, the case was followed up after 28 and 56 days to record clinical outcome.

For the repeated sero-survey, randomly selected participating household members from three age strata (0–17, 18–49, and ≥50 years) were visited every three months during one year to collect dried blood spots from a finger prick and (from 31 March 2021 onwards) record prior COVID-19 vaccination.

Laboratory procedures

To confirm COVID-19 in possible cases detected within the biweekly follow up of households, nasal swabs were self-administered at cases’ homes or assisted by interviewers in cases under 5 years of age, then transported in RNA ShieldTM reagent. Real-time reverse-transcription PCR was performed within the same day at Instituto Nacional de Saúde, Marracuene, Mozambique.

To determine SARS-CoV-2 seropositivity within the repeated sero-surveys, dried blood spots were collected, containing 450μl of blood sampled from a fingerprick in six circles (each approximately 75ul) on dried blood spot filter paper (Whatman 903TM Protein Saver Card). Samples were prepared for testing by punching two discs of 4mm diameter (corresponding to 40 μl of blood), and eluted overnight in 160 μL of hypertonic phosphate buffered saline-BSA (dilution 1:40, phosphate buffered saline-1% BSA-0.15% Tween, pH 7.4, Sigma-Aldrich). Before use in the immunoassay, eluted samples have been further diluted to 1:200 in hypertonic phosphate buffered saline-BSA, according to Mariën et al[12]. We then used an in-house developed multiplex antibody assay for the detection of anti-SARS-CoV-2 IgG. We coupled recombinant large spike glycoprotein S1 and S2 subunit, receptor-binding domain (RBD), and nucleocapsid-protein (NP) antigens derived from SARS-CoV-2 at Sino Biological to maximum of 1.25 × 10^6 paramagnetic MAGPLEX COOH-microsphere beads from Luminex Corporation as antibody targets. 150 μl of beads and diluted sera were added to each well, incubated at room temperature, then washed with 200 μl/well of hypertonic phosphate buffered saline-BSA. Adding biotin-labelled anti-human secondary IgG and streptavidin-R-phycoerythrin conjugate, another 30 min incubation, samples were read on Luminex MagPixTM at Instituto Nacional de Saúde, Marracuene, Mozambique. For each antigen target, a cut-off value of antibody detection was estimated by adding 2.5 standard deviations to the average value of 42 negative control samples from residents of Maputo, collected prior to the pandemic and also spotted on filter paper. We used two criteria to determine seropositivity: (i) both RBD and NP above the cut-off, ensuring excellent specificity as demonstrated in [12], and (ii) RBD above the cut-off, similar to assays used in most other SARS-CoV-2 sero-surveys [7]. After breakdown of the MagPixTM platform at Instituto Nacional de Saúde, serological testing for samples collected after August 2021 became unavailable.

Dried blood spot cards containing unused blood spots and aliquots of nasal swab samples were stored in -80°C freezers at Instituto Nacional de Saúde and will be destroyed after five years.

Data analysis

We estimated incidence rates of acute respiratory illness and of COVID-19 from respectively the number of possible COVID-19 cases and of confirmed COVID-19 cases, divided by the observation time. Because every household visit recorded possible cases with onset during two weeks before the visit, observation time consisted of the two weeks prior to each visit, or the time between visits if less than two weeks spanned between consecutive visits. We analysed clinical signs and symptoms associated with COVID-19, comparing confirmed cases to possible cases testing negative for SARS-CoV-2, adjusting for age using unconditional logistic regression.

To identify participant demographic, health, socio-economic and behavioural characteristics associated with COVID-19, we did a survival analysis fitting a Cox proportional hazards model with self-reported first confirmed COVID-19 as event variable, and observation time, censored after a first confirmed COVID-19 episode, as time variable, adjusting for age and sex.

We estimated infection- and vaccination-induced SARS-CoV-2 seroprevalence, by age group, based on sero-survey samples collected up to 31 July 2021. Samples were SARS-CoV-2 sero-positive when antibodies against RBD and NP were detected, as proposed by a validation study of the assay [12]. To ensure comparability to results with other sero-surveys, we also analysed seroprevalence based on antibodies against RBD only.

To identify participant characteristics associated with SARS-CoV-2 infection (including asymptomatic), similar to the above survival analysis of first symptomatic COVID-19, we fitted a Cox proportional hazards model to sero-survey participants with ≥ 2 samples collected up to 31 July 2021. SARS-CoV-2 infection (event variable) was defined as either a SARS-CoV-2 positive result following a negative result (sero-conversion), or an initial SARS-CoV-2 positive result. The time variable consisted of three months prior to each sero-survey, or the time between consecutive sero-surveys if less than three months spanned in-between, and was–in case of sero-conversion–censored at the midpoint between the last negative test and the subsequent positive test.

Ethical considerations

The study protocol and amended protocol (adding COVID-19 vaccination to case report forms) were approved by Institutional Review Boards of the Institute of Tropical Medicine and of Instituto Nacional de Saúde, the National Committee for Bioethics in Health of Mozambique (CNBS; Comité Nacional De Bioética para Saúde, 517/CNBS/2020) and the Antwerp University Hospital ethics committee (B3002020000123). The study obtained administrative approval by the Minister of Health and the Health authorities of the Municipal Council, through cover letters of the study. Study participants provided written informed consent at baseline for study participation, and again at the time of collecting a nasal swab or at the first sero-survey visit. For minors, written informed consent was asked to parents or guardians, on top of a written assent form for 12 to 18 year old participants. In case of illiteracy, a fingerprint from the participant and a signature from a witness (person ≥18 years old, not part of the study team) were obtained.

Results

Household surveillance of acute respiratory illness

Between 15 December 2020 and 31 March 2021, we conducted 11,925 household visits in 1,561 households, covering 6,049 participants (Fig 1). Participants were median 21 years old (interquartile range, IQR, 11–38 years), 3,315 (54.8%) were female, and 435 (7.3%) disclosed to be HIV positive. 2,694 (55.6% of 4,841 with recorded socio-economic status) did not complete primary education and 93 (1.9%) had higher education.

Fig 1. Household acute repiratory illness and COVID-19 surveillance.

Fig 1

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A. Weekly frequency of household visits, B. Geographical distribution of household visits in Maputo City, C. Weekly number of possible COVID-19 cases, stacked by SARS-CoV-2 PCR test result, D. Geographical distribution of possible COVID-19 cases by result. Possible cases were not tested if a nasal swab could not be correctly collected and transported to the reference laboratory. Maps were made in R using the ggmap package and map tiles by Stamen Design, under CC BY 4.0. Data by OpenStreetMap, under ODbL.

Respiratory illness and COVID-19 incidence rate

In the two weeks prior to the visits, 482 (30.9%) households reported at least one possible case in the household. The incidence rate of respiratory illness was 364.5 (95% CI 352.8–376.1) per 1,000 person-years (py, 691 possible cases in 611 participants; 1,895.9 py followed up). Of 579 possible cases, a nasal swab was collected and tested, median 5 days (IQR, 3–8 days) after symptom onset. SARS-CoV-2 was confirmed in 144 (24.9%) cases. The incidence rate of confirmed COVID-19 was 72.2 (95% CI 60.6–83.9) per 1,000 py. Among participants under 18 years old, this was 25.9 (95%CI 15.0–36.8) per 1,000 py; in 18–49 year olds it was 79.9 (95%CI 61.2–98.5) per 1,000 py; in ≥50 year olds, it was 188.3 (95%CI 141.8–234.9) per 1,000 py. SARS-CoV-2 positivity of tested possible cases peaked at 38.2% in January 2021, at 42.2% in July 2021, and at 53.1% in December 2021.

Clinical signs and symptoms of mild and moderate COVID-19

Reported COVID-19 cases were median 36.4 years old (IQR 22.3–57.5 years) and 87 (60.4%) were female (Table 1). Compared to SARS-CoV-2 negative cases (median age 26.0 years, IQR 10.8–49.3, 55.8% female), COVID-19 cases had more frequently anosmia (age-adjusted odds ratio, aOR 2.36 95%CI 1.48–3.58), ageusia (aOR, 2.29 95%CI 1.45–3.58), loss of appetite (aOR 2.21 95%CI 1.37–3.56), and chills (aOR 1.78 95%CI 1.05–2.97). During the Omicron variant wave starting December 2021, the association with each of these symptoms disappeared (anosmia aOR 1.1 95%CI 0.46–2.56, ageusia 0.70 95%CI 2.29–1.62, loss of appetite 1.25 95%CI 0.52–2.96, chills 0.88 95%CI 0.28–2.49).

Table 1. Clinical signs and symptoms associated with SARS-CoV-2 confirmation among acute respiratory illness (possible COVID-19 cases) reported during December 2020-March 2022, using unconditional logistic regression to estimate age-adjusted and crude odds ratios.

Factors Confirmed SARS-CoV-2 (N = 144) Negative SARS-CoV-2 (N = 435) Crude odds ratio Age-adjusted odds ratio
n % n % OR 95%CI aOR 95% CI
Age*: 0–9 years 7 4.9 90 21.5 ref
    10–19 years 18 12.5 79 18.9 2.93 1.21–7.87
    20–29 years 34 23.6 62 14.8 7.05 3.10–18.3
    30–39 years 18 12.5 48 11.5 4.82 1.95–13.2
    40–49 years 14 9.7 37 8.8 4.86 1.87–13.8
    50–59 years 24 16.7 46 11.0 6.71 2.82–17.9
    60–69 years 22 15.3 40 9.5 7.07 2.92–19.1
    70+ years 7 4.9 17 4.1 5.29 1.62–17.4
Sex*: Female 87 60.4 234 55.8 1.21 0.82–1.78 1.19 0.81–1.77
Clinical signs/symptoms
    Cough 117 89.3 326 86.0 1.36 0.75–2.63 1.52 0.82–2.95
    Headache 81 61.8 217 57.3 1.21 0.81–1.82 1.14 0.75–1.73
    Rhinorrhoea 69 52.7 221 58.3 0.80 0.53–1.19 0.86 0.57–1.29
    Sore throat 54 41.2 131 34.6 1.33 0.88–1.99 1.22 0.80–1.84
    Ageusia 47 35.9 69 18.2 2.51 1.61–3.91 2.29 1.45–3.58
    Oxygen saturation <95% 16/48 33.3 36/151 23.8 1.60 0.78–3.22 1.54 0.74–3.14
    Anosmia 43 32.8 63 16.6 2.45 1.55–3.85 2.36 1.48–3.75
    Fatigue 41 31.3 95 25.1 1.36 0.88–2.10 1.26 0.80–1.96
    Loss of appetite 39 29.8 62 16.4 2.17 1.36–3.44 2.21 1.37–3.56
    Fever 33 25.2 96 25.3 0.99 0.62–1.56 1.10 0.68–1.75
    Chills 29 22.1 50 13.2 1.87 1.12–3.10 1.78 1.05–2.97
    Joint pain 29 22.1 49 12.9 1.91 1.14–3.17 1.59 0.90–2.59
    Chest pain 25 19.1 60 15.8 1.25 0.74–2.08 1.10 0.64–1.85
    Myalgia 24 18.3 49 12.9 1.51 0.87–2.56 1.24 0.70–2.13
    Nausea 10 7.6 23 6.1 1.28 0.57–2.69 1.29 0.57–2.77
    Dyspnoe 9 6.9 36 9.5 0.70 0.31–1.44 0.62 0.27–1.31
    Diarrhoea 8 6.1 26 6.9 0.88 0.37–1.92 0.86 0.35–1.89
    Vomit 7 5.3 19 5.0 1.07 0.41–2.50 1.32 0.49–3.23
    Rash 3 2.3 3 0.8 2.94 0.54–16.0 2.98 0.54–16.4
    Nose bleeding 1 0.8 3 0.8 0.95 0.05–7.50 0.99 0.05–7.94
    Change of consciousness 0 0.0 3 0.8
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* age and sex missing of 16 possible cases (all SARS-CoV-2 negative), clinical signs and symptoms missing of 69 possible cases (56 SARS-CoV-2 negative, 13 positive).

Of 92 confirmed COVID-19 cases followed up after 28 days, of whom 54 again after 56 days, one (1.1%) died.

Characteristics associated with symptomatic COVID-19

Increasing age (in ≥70 year olds hazard ratio (HR) 10.2, 95%CI 3.58–29.09) and several reported comorbidities increased the risk of symptomatic COVID-19: leukaemia, chronic lung disease, overweight, and hypertension (Table 2). We found no increased risk of COVID-19 in people with HIV (HR 0.96, 95%CI 0.45–2.04) or with (a history of) tuberculosis (HR 1.06, 95%CI 0.38–2.96). Households with no or limited handwashing facilities members (HR 0.54, 95%CI 0.34–0.87) and with bedrooms shared between 3 or more household members (HR 0.45, 95%CI 0.26–0.76), were less likely to report COVID-19.

Table 2. Demographic, socio-economic and behavioural characteristics associated with first confirmed COVID-19 among among acute respiratory illness (possible COVID-19 cases) reported in population-based surveillance during December 2020-March 2022, using a Cox regression model adjusting for age and sex.

Characteristic Cohort participants Reported first COVID-19 COVID-19 age-/sex-adjusted hazard ratio
N % N % HR 95%CI
Age 0–9 years 1331 22.0 7 5.1 ref
10–19 1570 26.0 18 13.1 2.17 0.91–5.20
20–29 1128 18.6 30 21.9 5.01 2.20–11.40
30–39 644 10.6 17 12.4 5.13 2.13–12.37
40–49 519 8.6 14 10.2 5.03 2.03–12.47
50–59 406 6.7 24 17.5 11.05 4.76–25.65
60–69 318 5.3 20 14.6 11.81 4.99–27.93
≥70 133 2.2 7 5.1 10.20 3.58–29.09
Sex Male 2804 46.4 55 40.1 ref
Female 3245 53.6 82 59.9 1.18 0.84–1.67
Socio-economic quintile*§ 1st (lowest) 429 14.6 5 4.8 0.22 0.09–0.57
2nd 579 19.7 24 22.9 0.83 0.50–1.39
3rd 591 20.1 12 11.4 0.38 0.20–0.72
4th 640 21.7 26 24.8 0.80 0.48–1.31
5th (highest) 706 24.0 38 36.2 ref
Education*§ None 1350 41.3 53 47.3 0.96 0.44–2.13
Primary 1557 47.6 48 42.9 1.06 0.50–2.26
Secondary 276 8.4 8 7.1 ref
Higher 88 2.7 3 2.7 1.04 0.28–3.95
Health worker§ 130 3.8 4 5.9 1.46 0.53–4.02
Reported comorbidities HIV 450 7.5 8 10.0 0.96 0.45–2.04
(history of) tuberculosis 179 3.0 4 5.1 1.06 0.38–2.96
hypertension 583 9.7 22 27.8 1.91 1.05–3.48
diabetes 68 1.1 3 3.8 1.78 0.55–5.82
asthma 291 4.9 4 5.1 1.16 0.42–3.19
chronic lung disease 37 0.6 4 5.1 8.11 2.91–22.58
chronic heart disease 54 0.9 2 2.5 1.90 0.46–7.85
leukaemia 4 0.1 1 1.3 33.47 4.48–249.94
BMI# underweight 795 37.2 12 15.8 1.45 0.68–3.13
normal 830 38.8 27 35.5 ref
overweight 281 13.1 19 25.0 1.87 1.02–3.44
obesity 231 10.8 18 23.7 2.09 1.08–4.06
Smoking non smoker 5738 95.8 74 93.7 ref
(ex-)smoker 251 4.2 5 6.3 1.10 0.43–2.85
Public transportation none 3948 66.0 39 49.4 ref
bus/train 2013 33.7 40 50.6 1.24 0.78–1.96
moto taxi/shared taxi 19 0.3 0 0.0
Sharing bedroom 1–2 pers. 3311 55.6 61 77.2 ref
3 or more pers. 2646 44.4 18 22.8 0.45 0.26–0.76
Toilet in the house 5061 85.0 64 81.0 ref
shared between households 896 15.0 15 19.0 1.42 0.81–2.49
Handwash facility sink/faucet 1748 29.3 35 44.3 ref
bucket/jar/kettle 1204 20.2 9 11.4 0.39 0.19–0.81
none 3005 50.4 35 44.3 0.54 0.34–0.87
Water available in house yes 2153 36.1 35 44.3 ref
no 3804 63.9 44 55.7 0.74 0.48–1.16
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*level of education (of the mother among children and adolescents) and socio-economic level have been measured as part of the HDSS round in 2019 and was available for 4746 household members.

§ in ≥ 18 year olds.

#in ≥16 year olds

Infection-induced SARS-CoV-2 seroprevalence

2185 samples collected until 31 July 2021 of 1412 sero-survey participants (median age 30.6 years, IQR 13.7–57.6; 38.2% ≥50 years old; 55.2% female) were tested. 301 participants (21.3%) tested positive (antibodies against RBD and NP) at least once. 34 (45.3%) out of 75 with a test subsequent to positive test, sero-reverted.

Crude seroprevalence increased from 4.8% (95%CI 1.1–8.6) in December 2020 to 34.2% (95%CI 23.4–45.1) in June 2021, when 2.7% of participants reported vaccination with at least one dose of vaccine (Fig 2). Seroprevalence increased strongest in ≥50 year olds, peaking at 51.6% (95%CI 34.0–69.2) in June 2021, when 3.2% was vaccinated, and then declined to 41.6% (95%CI 26.5–56.7) in July 2021, when 10.9% was vaccinated.

Fig 2. Infection- and vaccine-induced SARS-CoV-2 seroprevalence by age group, December 2020—July 2021.

Fig 2

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N0-17 years = 647, N18-49 years = 612, N≥50 years = 882. Whether SARS-CoV-2 sero-positivity was infection- or vaccine-induced was based on self-reported prior COVID-19 vaccination, assuming SARS-CoV-2 sero-conversion within 5 months after receiving at least one COVID-19 vaccine was due to the vaccine.

Crude seroprevalence based on antibodies against RBD only was higher, rising from 10.5% (95%CI 5.1–15.9%) in December 2020 to 46.5% (95%CI 36.7–56.3) in July 2021, without decrease in seroprevalence from June to July 2021 (S1 Table).

Characteristics associated with SARS-CoV-2 infection

Older age increased the risk of SARS-CoV-2 infection (HR 60–69 versus 0–9 years 1.57, 95%CI 1.03–2.39, Table 3). We found no association between SARS-CoV-2 infection and socio-economic, behavioural factors, nor comorbidities.

Table 3. Demographic, socio-economic and behavioural characteristics associated with SARS-CoV-2 infection (including asymptomatic) among sero-survey participants with ≥ 2 samples tested during December 2020-July 2021, using a Cox regression model adjusting for age and sex.

Characteristic Sero-survey participants SARS-CoV-2 infected SARS-CoV-2 age-/sex-adjusted hazard ratio
N % N % HR 95%CI
Age 0–9 years 223 15.9 35 12.2 ref
10–19 305 21.7 58 20.2 1.11 0.73–1.69
20–29 161 11.5 28 9.8 0.93 0.56–1.53
30–39 114 8.1 14 4.9 0.82 0.44–1.53
40–49 68 4.8 15 5.2 1.11 0.61–2.04
50–59 240 17.1 54 18.8 1.32 0.86–2.03
60–69 202 14.4 57 19.9 1.57 1.03–2.39
≥70 93 6.6 26 9.1 1.20 0.72–2.00
Sex Male 630 44.8 128 44.6 ref
Female 776 55.2 159 55.4 0.94 0.74–1.18
Socio-economic quintile*§ 1st (lowest) 116 14.0 31 14.5 1.06 0.68–1.65
2nd 152 18.3 46 21.5 1.41 0.95–2.09
3rd 161 19.4 48 22.4 1.22 0.82–1.81
4th 173 20.9 34 15.9 0.77 0.50–1.18
5th (highest) 227 27.4 55 25.7 ref
Education*§ None 502 54.3 149 61.3 1.01 0.57–1.79
Primary 334 36.1 72 29.6 0.89 0.51–1.55
Secondary 65 7.0 16 6.6 ref
Higher 23 2.5 6 2.5 1.13 0.44–2.92
Health worker§ 27 4.1 3 1.9 0.64 0.28–1.45
Reported comorbidities HIV 118 12 20 10.9 0.82 0.51–1.32
(history of) tuberculosis 47 4.8 7 3.8 0.87 0.40–1.86
hypertension 209 21.2 49 26.8 0.91 0.61–1.36
diabetes 27 2.7 11 6 1.65 0.88–3.11
asthma 59 6.0 14 7.7 1.23 0.71–2.12
chronic lung disease 6 0.6 2 1.1 2.48 0.61–10.09
chronic heart disease 12 1.2 1 0.5 0.40 0.06–2.87
leukaemia 1 0.1 1 0.5 1.27 0.17–9.24
BMI# underweight 258 29.5 52 26.8 0.72 0.35–1.46
normal 352 40.3 69 35.6 ref
overweight 126 14.4 30 15.5 1.08 0.69–1.70
obesity 138 15.8 43 22.2 1.25 0.81–1.93
Smoking non smoker 927 94 172 94 ref
(ex-)smoker 59 6 11 6 0.67 0.35–1.27
Public transportation none 587 59.6 109 59.9 ref
bus/train 395 40.1 71 39.0 0.85 0.63–1.16
moto taxi/shared taxi 3 0.3 2 1.1 1.95 0.47–8.07
Sharing bedroom 1–2 pers. 805 58.7 178 63.6 ref
3 or more pers. 566 41.3 102 36.4 0.84 0.66–1.08
Sharing toilet with other household 214 15.6 37 13.2 0.80 0.57–1.13
Handwash facility sink/faucet 511 37.3 110 39.3 ref
bucket/jar/kettle 267 19.5 51 18.2 1.11 0.80–1.55
none 593 43.3 119 42.5 0.98 0.75–1.27
Water available in house yes 581 42.4 118 42.1 ref
no 790 57.6 162 57.9 1.08 0.85–1.37
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*level of education (of the mother among children and adolescents) and socio-economic level have been measured as part of the HDSS round in 2019.

§ in ≥ 18 year olds.

#in ≥16 year olds.

Discussion

Population-based COVID-19 surveillance in an urban population cohort in Mozambique confirmed that even during the acute phase of the pandemic the large majority of SARS-CoV-2 infections were asymptomatic, symptomatic cases were mild, and three in four were non-febrile.

Three COVID-19 peaks were distinct and died out after a few weeks, while other respiratory illness (SARS-CoV-2 negative cases) continued to be reported throughout 2021. Sudden drops in COVID-19 incidence after peaks while respiratory pathogens other than SARS-CoV-2 continue to circulate, indicate that newly introduced COVID-19 variants (Alpha, Delta, Omicron) could have quickly spread despite non-pharmaceutical interventions. Nonetheless, transmission slowed when infection-induced seroprevalence (e.g., 11.2% in March 2021) was still lower than the herd immunity threshold anticipated from the Alpha variants’ reported transmissibility [13].

Surveillance started in December 2020 when the Beta variant had spread for 3 months through neighbouring South Africa, and two weeks before a surge in cases was detected in facility-based disease surveillance in Mozambique. Infection-induced seroprevalence of 4.8% in December 2020 was lower than the corrected pooled 16.2% reported in other African countries that month [7]. Limited spread of SARS-CoV-2 before January 2021 was also supported by facility-based COVID-19 surveillance and by bed occupancy in COVID-19 management facilities. Even with limited confirmatory testing of cases, neither PCR testing nor hospital bed capacity have been overwhelmed until January 2021, supporting the low seroprevalence observed in December 2020. Limited spread of wild type virus and the Beta variant during the first year of the pandemic–contrasting to neighbouring South Africa and Eswatini–could result from limited seeding through imported cases, limited mobility within the city and within the country, and longer maintained non-pharmaceutical interventions (e.g., workplace closure)–even if less stringent–compared to its neighbours [14]. The eventual surge in cases in January 2021 followed relaxed non-pharmaceutical interventions for the end-of-year holidays, including partial lifting of travel restrictions, in turn resulting in many migrant workers returning from South Africa to households in Maputo. Increased (cross-border) mobility and increased social contacts coincided with the presumed introduction of the Alpha variant with increased transmissibility [13].

SARS-CoV-2 seroprevalence rose to 34.7% in June 2021, still far below the pooled 76% infection-induced seroprevalence reported in other African countries. Only a fraction of that difference in seroprevalence can be explained by different serological test specificity. Our analysis of SARS-CoV-2 sero-positivity comparing several SARS-CoV-2 antigen targets demonstrated a difference of up to 12%, thus cannot account for the twice higher seroprevalence in other sero-surveys in sub-Saharan Africa. A diagnostic performance study of the serological immunofluorescence assay supported the use of RBD and NP for IgG detection [12]. A study using the same assay however showed decreasing seroprevalence as a result of waning NP-specific IgG after three months [15]. This could explain the decreasing seroprevalence observed in July 2021.

The observed effect of age, obesity, and chronic conditions on the risk of mild disease was similar to the effect on risk of severe disease or death reported elsewhere [3,16]. While HIV and (history of) tuberculosis have been associated with COVID-19-related death [8], we observed no increased risk of infection nor of disease. Also, deprivation, increasing the risk of infection, disease and severity in several settings [3,4,17], did not affect the risk of SARS-CoV-2 infection in this population of Maputo city. In contrast, several indicators of deprivation, such as belonging to the lowest wealth quintile, lack of formal education, absence of handwash facilities, were associated with a lower risk of COVID-19. We are however hesitant to overinterpret these paradoxical findings, considering deprivation could influence voluntary self-reporting of illness, introducing a reporting bias. Among cases of respiratory illness, only anosmia, ageusia, loss of appetite and chills increased the probability of COVID-19, yet none of those symptoms was reported by more than a third of cases and the association disappeared in cases from December 2021 onwards, presumably Omicron cases. Symptoms’ poor predictive value, in combination with continued reporting of other respiratory illness, hampered diagnosis of mild/moderate COVID-19 on clinical grounds only [18].

Limitations of the study include the consecutive enrolment of households which already participated in the Polana Caniço HDSS, possibly introducing a selection bias of households where an adult member is present at home, or more willing to participate in and adhere to public health measures. Second, the population within the Polana Caniço HDSS might not fully reflect the wider population of Maputo or of Mozambique, and be more homogenous. We have been careful generalising findings to those larger populations. Differences in SARS-CoV-2 risk within the study population could be smaller than those in the general population. Third, because participating household members might tend to alter their behaviour in response to being followed-up, the so-called Hawthorne effect, we have been careful interpreting reported behaviour, and decided against describing a potentially biased number of reported contacts or reported mask wearing. Fourth, self-reporting might result in an underestimated prevalence of health conditions, e.g., HIV status, smoking. We therefore analysed health conditions only when comparing cases to the study population, in which underreporting might affect both groups similarly. Nevertheless, the association could be underestimated. Finally but importantly, self-reporting of respiratory symptoms likely suffers from underreporting, for a number of reasons including poor recall, absent household members at the time of a visit, or fear of medical procedures or healthcare costs following the reporting of symptoms. Different subgroups could also have a different likelihood to self-report symptoms. The incidence of respiratory illness and of COVID-19 should be carefully interpreted and might underestimate the actual incidence.

Active surveillance in an urban population cohort confirmed frequent COVID-19 underreporting, yet indicated that even in the first years of the pandemic, the large majority of cases were mild and non-febrile. In contrast to industrialised countries, socio-economic deprivation did not increase the risk of infection nor disease.

Supporting information

S1 Checklist. Inclusivity in global research.

(DOCX)

pgph.0003550.s001.docx (64KB, docx)
S1 Table

(DOCX)

pgph.0003550.s002.docx (59.1KB, docx)

Acknowledgments

We thank participants of the Polana Caniço HDSS, interviewers, teams involved in laboratory testing of samples (Claudia Machume, Gercio Cuamba, Caro Van Geel), data management (Alberto Machaze, Eben Matavele, Harry van Loen), and study monitors (Dimpall Asmucrai, Carolien Hoof).

Data Availability

Pseudonymized data supporting the findings of this study/publication are retained at the Institute of Tropical Medicine, Antwerp and can be made available after approval of a motivated and written request to ITMresearchdataaccess@itg.be. Study protocol, scripts for conducting the analysis, and anonymized data, without geo-located or other data that could allow identification, are available on https://github.com/ingelbeen/africover-git.

Funding Statement

The work was funded by the European & Developing Countries Clinical Trials Partnership (EDCTP, RIA2020EF-3031 to BI). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLOS Glob Public Health. doi: 10.1371/journal.pgph.0003550.r001

Decision Letter 0

Nei-yuan (Marvin) Hsiao

Transfer Alert

This paper was transferred from another journal. As a result, its full editorial history (including decision letters, peer reviews and author responses) may not be present.

10 Jun 2024

PGPH-D-24-00678

Mild and moderate COVID-19 during Alpha, Delta and Omikron pandemic waves in urban Maputo, Mozambique, December 2020-March 2022: a population-based surveillance study

PLOS Global Public Health

Dear Dr. Ingelbeen,

Thank you for submitting your manuscript to PLOS Global Public Health. After careful consideration, we feel that it has merit but does not fully meet PLOS Global Public Health’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please ensure the 3 necessary areas (sampling, epi comparison and study limitations) is adequately addressed, in the revised manuscript. The other recommended corrections raised by the reviewers should be carefully assessed and provide adequate explanation in the rebuttal should revision not possible or warranted.

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We look forward to receiving your revised manuscript.

Kind regards,

Nei-yuan (Marvin) Hsiao

Academic Editor

PLOS Global Public Health

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Additional Editor Comments (if provided):

The study provides valuable insight into SARS-CoV-2 in Mozambique where there is a relatively paucity of COVID-19 epidemiological data. The reviewers had provides valuable comment which though minor, can significantly strengthen the manuscript.

Please pay particular attention to the following area when addressing the reviewer's comments:

1. Sampling strategy and its impact on interpretation of finding.

2. In discussion, the difference of the wave/epi pattern of Mozambique with its neighbouring countries warrant some comments.

3. A robust study limitations section, particularly related to sampling strategy, is needed.

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Reviewer #1: Yes

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #2: Yes

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Reviewer #1: Review of

Mild and moderate COVID-19 during Alpha, Delta and Omikron pandemic waves in urban Maputo, Mozambique, December 2020-March 2022: a population-based surveillance study

General comments:

This paper presents a epidemiological study about mild and moderate COVID-19 occurrence in Mozambique proceeded through a population-based surveillance

General comments

� Thank you for stating the following financial disclosure and Acknowledgments Section and to provide a repository information for your data, codes and maps.

� Please, check if the keywords were included in DeCS/MeSH

Introduction

� Thanks for the introduction, it is very well written, easy to read and presents what is necessary on the topic. Authors may choose to discreetly include information about study locations, for example, population size.

� Please check grammar of sentence in third paragraph. Use commas to numbers.

� I understood that in Sep 2021 5% received at least 1 dose, and that 6 months later there was an increase to 40% with 1 dose, is this correct? It would be good to place more emphasis on vaccination coverage.

� Why Omicron was spelled with K, not C (for English)?

Methods

� In the second paragraph it would be delimited as a section "data collection" better describing the tools for the two studies (i) socio-economic questionnaire, (ii) questionnaire to collect symptoms and (iii) self-administered biological samples. Please also explain whether the questionnaires were different for each age group.

� Were questions about vaccination collected or did population coverage be used to interpret the results?

� I suggest that the authors describe better the definition of suspected cases (possible cases) including a sentence answering this question: What happens if the covid case is not confirmed, is it a negative PCR that was used to confirm the case or rule it out? Even with a well-reported clinic? see an example of how well you defined seropositivity (line 110). Even though the data analysis section perfectly indicates procedures to do that, it would be good to define it in a simpler way here.

� It was not clear to me whether, when there was a positive case, other residents of the same residence were tested even if they were asymptomatic, close contact was not a possible case? Can you explain this better here, in the methods section before appears in the next sections?

� Can you explain why close contact was not a possible case? I understand that this is mild and moderate covid, but it would be nice to inform you if there were asymptomatic cases or if this was not considered in this study. As you pointed in the discussion.

Laboratory procedures

� Laboratory procedures is a little difficult to follow because it is a very long paragraph, I suggest dividing and removing unnecessary punctuation that divides sentences like ( : ) on line 100.

� I missed the reference of the collections in each study, is difficult to follow, especially in time.

� What was done with the samples after they were tested? Stored? for how long, destroyed?

� Line 99, move citation to reference, following the journal's rules. Name (year) [ref]

Data analysis

� It's very good! It's very good! I only have a question, is the prevalence adjusted for the tests sensitivity/specificity?

� Previous, the methods need specifying better the outcomes. Define and re-specify your outcomes, presenting all your variables in clear terms.

Results

� You can include a comma in the numbers presented in the text, it is easier to read. (line 149-153)

� HIV diagnosis or comorbidities were self-reported? Please include this information in the methods section as a case definition.

� In line 151-152, I don't understand who recorded socio-economic status, does information only apply to over 18yo for example? Please move this information, clarifying this doubt, to the methods section. Please answer the following question very simply: Considering that the study includes people of all ages, are the educational level results for those over 18? (line152-153)

� Figure 1, can you explain why some people were not tested?

� Please, include in all foot tables the name of the test used in the presented aOR, OR, HR (...)

� Table 1 - replace throat pain for sore throat.

� Figure 2, It is not very clear if “positive after vaccination” refers to vaccine-induced antibody +, please, consider replace the text for meaning is clear.

� Line 181 there is no need to parentheses.

�

Discussion/Conclusion

� Thanks for the discussion section, its drawn appropriately based on the data presented.

� Please remove the parentheses of (symptomatic) on line 219, the sentence is confusing.

� Review line 253

� Did the authors observe any limitation? It would be nice to comment on in the discussion section. Please explain whether these limitations have been mitigated and how you plan to address them. Otherwise, authors can discuss any participation issue in the limitations section.

� There are few spelling errors that need to be revised.

Reviewer #2: While interest in SARS-CoV-2 has waned with time, the manuscript provides valuable insight into trying to understand the impact of the pandemic in sub-Saharan Africa, and warrants publication. There are however, a few issues that need to be addressed:

1. It is unclear how participants were selected from the HDSS for the 2 weekly follow-ups, and what if any sampling strategy was used to recruit them.

2. An introduction to the HDSS population and description of the setting would be useful. My concern is that if the population were very homogeneous in terms of socioeconomic status, it would be difficult to pick up any differences in SARS-CoV-2 epidemiology with the current population size.

3. The aHR values for socioeconomic quintiles and education in Table 3 are missing. These results are crucial to the findings of the study, and need to be reported.

4. Neighboring South Africa experienced a massive wave of SARS-Cov-2 infections in June/July 2020, and again in December 2020. As official case numbers under-counted the real extent of the pandemic, is it possible that Mozambique experienced mild SARS-CoV-2 in the middle of 2020, before the survey was started, and with the waning of antibody levels this "first" wave was missed? Either way, further interrogation of the lower seroprevalence results found in Maputo is needed, as the authors do not provide a sufficient explanation. The argument that prolonged NPI prevented transmission (line 233), might in true with regards to other neighbouring countries, but in the reference no 14 South Africa is noted to have stricter policies than Mozambique, contradicting the authors' explanation.

5. Line 252-253: "This discrepancy would be in line with observed lower pathogenicity in other sSA studies" - reference is needed.

6. Line 247-248: No relationship between HIV and COVID-19 death was found. But how was HIV status ascertained? Was it only through respondent self-reporting, in which case exposure status misclassification might underestimate the relationship. I am not sure what the current HIV prevalence for adults in Mozambique is, but presume it is higher than the 7.5% reported amongst study participants.

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Reviewer #1: Yes: Fabiana Ganem

Reviewer #2: Yes: Hannah Hussey

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PLOS Glob Public Health. doi: 10.1371/journal.pgph.0003550.r003

Decision Letter 1

Nei-yuan (Marvin) Hsiao

10 Jul 2024

Mild and moderate COVID-19 during Alpha, Delta and Omicron pandemic waves in urban Maputo, Mozambique, December 2020-March 2022: a population-based surveillance study

PGPH-D-24-00678R1

Dear Dr Ingelbeen,

We are pleased to inform you that your manuscript 'Mild and moderate COVID-19 during Alpha, Delta and Omicron pandemic waves in urban Maputo, Mozambique, December 2020-March 2022: a population-based surveillance study' has been provisionally accepted for publication in PLOS Global Public Health.

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Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Global Public Health.

Best regards,

Nei-yuan (Marvin) Hsiao

Academic Editor

PLOS Global Public Health

***********************************************************

Reviewer Comments (if any, and for reference):

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Checklist. Inclusivity in global research.

    (DOCX)

    pgph.0003550.s001.docx (64KB, docx)
    S1 Table

    (DOCX)

    pgph.0003550.s002.docx (59.1KB, docx)
    Attachment

    Submitted filename: PGPH_C19.docx

    pgph.0003550.s003.docx (32.6KB, docx)
    Attachment

    Submitted filename: Response to Reviewers_mvds.docx

    pgph.0003550.s004.docx (40.8KB, docx)

    Data Availability Statement

    Pseudonymized data supporting the findings of this study/publication are retained at the Institute of Tropical Medicine, Antwerp and can be made available after approval of a motivated and written request to ITMresearchdataaccess@itg.be. Study protocol, scripts for conducting the analysis, and anonymized data, without geo-located or other data that could allow identification, are available on https://github.com/ingelbeen/africover-git.

    Articles from PLOS Global Public Health are provided here courtesy of PLOS

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