\documentclass[10pt]{article}

\usepackage{fullpage}
\usepackage{setspace}
\usepackage{parskip}
\usepackage{titlesec}
\usepackage[section]{placeins}
\usepackage{xcolor}
\usepackage{breakcites}
\usepackage{lineno}
\usepackage{hyphenat}





\PassOptionsToPackage{hyphens}{url}
\usepackage[colorlinks = true,
            linkcolor = blue,
            urlcolor  = blue,
            citecolor = blue,
            anchorcolor = blue]{hyperref}
\usepackage{etoolbox}
\makeatletter
\patchcmd\@combinedblfloats{\box\@outputbox}{\unvbox\@outputbox}{}{%
  \errmessage{\noexpand\@combinedblfloats could not be patched}%
}%
\makeatother


\usepackage{natbib}




\renewenvironment{abstract}
  {{\bfseries\noindent{\abstractname}\par\nobreak}\footnotesize}
  {\bigskip}

\titlespacing{\section}{0pt}{*3}{*1}
\titlespacing{\subsection}{0pt}{*2}{*0.5}
\titlespacing{\subsubsection}{0pt}{*1.5}{0pt}


\usepackage{authblk}


\usepackage{graphicx}
\usepackage[space]{grffile}
\usepackage{latexsym}
\usepackage{textcomp}
\usepackage{longtable}
\usepackage{tabulary}
\usepackage{booktabs,array,multirow}
\usepackage{amsfonts,amsmath,amssymb}
\providecommand\citet{\cite}
\providecommand\citep{\cite}
\providecommand\citealt{\cite}
% You can conditionalize code for latexml or normal latex using this.
\newif\iflatexml\latexmlfalse
\providecommand{\tightlist}{\setlength{\itemsep}{0pt}\setlength{\parskip}{0pt}}%

\AtBeginDocument{\DeclareGraphicsExtensions{.pdf,.PDF,.eps,.EPS,.png,.PNG,.tif,.TIF,.jpg,.JPG,.jpeg,.JPEG}}

\usepackage[utf8]{inputenc}
\usepackage[ngerman,greek,english]{babel}



\usepackage{float}








\begin{document}

\title{Seroprevalence of SARS-CoV-2 in 10 Regional Capitals of Cameroon,
October-December 2020}



\author[1]{Karampreet Sachathep}%
\author[1]{Tiffany Harris}%
\author[1]{Yen  Duong}%
\author[1]{Giles Reid}%
\author[2]{Emily Kainne  Dokubo}%
\author[2]{Judith  Shang}%
\author[2]{Clement  Ndongmo}%
\author[1]{Ekali Gabriel }%
\author[1]{G Tharp}%
\author[2]{Laura Dimite}%
\author[2]{Gordon Okpu}%
\author[1]{Francis Ogollah}%
\author[1]{Dubliss Nguafack}%
\author[1]{Martin Ntse}%
\author[1]{Gili Hrusa}%
\author[1]{Katherine Yuengling}%
\author[1]{Megan Tebbenhoff}%
\author[3]{Essomba René}%
\author[4]{Ngo Sack  Françoise}%
\author[4]{Naah Tabala  Felicity}%
\author[4]{Marie Claire Okomo Assoumou}%
\author[5]{Anne Bissek}%
\author[6]{Adama  N’Dir}%
\affil[1]{ICAP at Columbia University}%
\affil[2]{Centers for Disease Control and Prevention}%
\affil[3]{Ministry of Health, Republic of Cameroon}%
\affil[4]{Ministry of Health, Cameroon}%
\affil[5]{Cameron University}%
\affil[6]{CDC Cameroon}%


\vspace{-1em}



  
  \date{May 21, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
Cameroon was among the most affected African countries during the first
wave of the COVID-19 pandemic; however, the true prevalence of
SARS-CoV-2 remains unknown. From October-December 2020 we conducted a
cross-sectional, age-stratified SARS-CoV-2 seroepidemiological survey at
30 purposively selected community-based sites across Cameroon's 10
regional capitals, sampling 10,000 individuals aged 5 years or older. We
employed a parallel SARS-CoV-2 antibody testing algorithm (WANTAI ELISA
and Abbot Architect) to improve both the positive predictive value and
negative predictive value of seroprevalence. The overall weighted and
adjusted seroprevalence of SARS-CoV-2 antibodies across the 10 urban
capitals of Cameroon was 10.5\% (95\% CI: 9.1\%-12.0\%) among
participants aged [?]5 years. Of the 9332 participants, 730 males (13.1\%,
95\% CI: 11.5\%-14.9\%) had SARS-CoV-2 antibodies compared to 293
females (8.0\%, 95\% CI: 6.8\%---9.3\%). Among those who reported a
comorbidity at the time of testing, 15.8\% (95\% CI: 12.8\%-19.4\%) were
seropositive. We estimated that over 2 million SARS-CoV-2 infections
occurred in the 10 regional capitals of Cameroon between October and
December 2020, compared to 21,160 cases officially reported at that time
translating to one laboratory-confirmed case was reported for every 110
SARS-CoV-2 infections across the 10 urban capitals. This study's
findings point to extensive and under-reported circulation of SARS-CoV-2
in Cameroon-- an almost 100-fold more cases compared to the number of
cases reported to the World Health Organization. This finding highlights
the importance of conducting serosurveys, especially in settings where
access to testing may be limited and to repeat such surveys as part of
pandemic tracking.%
\end{abstract}%



\sloppy


\textbf{Seroprevalence of SARS-CoV-2 in 10 Regional Capitals of
Cameroon, October-December 2020}

Authors: Karampreet Sachathep \textsuperscript{1,2}, Yen T.
Duong\textsuperscript{1}, Giles Reid\textsuperscript{1}, Emily Kainne
Dokubo\textsuperscript{4,5}, Judith D. Shang\textsuperscript{5}, Clement
B. Ndongmo\textsuperscript{4,5}, Ekali Gabriel\textsuperscript{7}, G
Tharp\textsuperscript{3}, Laura Eno Dimite\textsuperscript{5}, Adama
N'Dir\textsuperscript{4,5}, Gordon Okpu\textsuperscript{5}, Francis M.
Ogollah\textsuperscript{1}, Dubliss Nguafack\textsuperscript{7}, Martin
C Ntse\textsuperscript{7}, Gili Hrusa\textsuperscript{1}, Katherine
Yuengling\textsuperscript{1}, Megan Tebbenhoff\textsuperscript{2} ,
Essomba Ren\selectlanguage{ngerman}é\textsuperscript{6}, Ngo Sack Françoise\textsuperscript{6},
Naah Tabala Felicity\textsuperscript{6}, Marie Claire
Okomo\textsuperscript{6}, Anne-Cecile Zoung-Kanyi
Bissek\textsuperscript{6} , Tiffany G. Harris\textsuperscript{1,2}.

Affiliations:

1-ICAP at Columbia University, New York, NY, USA

2-Department of Epidemiology, Mailman School of Public Health, Columbia
University, New York, NY, USA

3-Department of Sociomedical Sciences, Mailman School of Public Health,
New York, NY, USA

4-US Centers for Disease Control and Prevention, Atlanta, GA, USA

5-US Centers for Disease Control and Prevention, Cameroon

6-Ministry of Health, Yaoundé, Cameroon

7- ICAP in Cameroon, Yaoundé, Cameroon

\textbf{Acknowledgments}

This research project has been supported by the President's Emergency
Plan for AIDS Relief (PEPFAR) through the Centers for Disease Control
and Prevention (CDC) under the terms of NU2GGH002171.

\textbf{Disclaimer}

The findings and conclusions in this report are those of the authors and
do not necessarily represent the official position of the funding
agencies.

\textbf{Abstract}

\textbf{Background}

Cameroon was among the most affected African countries during the first
wave of the COVID-19 pandemic; however, the true prevalence of
SARS-CoV-2 remains unknown.

\textbf{Methods}From October-December 2020 we conducted a
cross-sectional, age-stratified SARS-CoV-2 seroepidemiological survey at
30 purposively selected community-based sites across Cameroon's 10
regional capitals, sampling 10,000 individuals aged 5 years or older. We
employed a parallel SARS-CoV-2 antibody testing algorithm (WANTAI ELISA
and Abbot Architect) to improve both the positive predictive value and
negative predictive value of seroprevalence.

\textbf{Results}The overall weighted and adjusted seroprevalence of
SARS-CoV-2 antibodies across the 10 urban capitals of Cameroon was
10.5\% (95\% CI: 9.1\%-12.0\%) among participants aged \selectlanguage{english}[?]5 years. Of the
9332 participants, 730 males (13.1\%, 95\% CI: 11.5\%-14.9\%) had
SARS-CoV-2 antibodies compared to 293 females (8.0\%, 95\% CI:
6.8\%---9.3\%). Among those who reported a comorbidity at the time of
testing, 15.8\% (95\% CI: 12.8\%-19.4\%) were seropositive. We estimated
that over 2 million SARS-CoV-2 infections occurred in the 10 regional
capitals of Cameroon between October and December 2020, compared to
21,160 cases officially reported at that time translating to one
laboratory-confirmed case was reported for every 110 SARS-CoV-2
infections across the 10 urban capitals.

\textbf{Conclusion}This study's findings point to extensive and
under-reported circulation of SARS-CoV-2 in Cameroon-- an almost
100-fold more cases compared to the number of cases reported to the
World Health Organization. This finding highlights the importance of
conducting serosurveys, especially in settings where access to testing
may be limited and to repeat such surveys as part of pandemic tracking.

\textbf{Key Words:} SARS-CoV-2, Serosurvey, Cameroon, COVID-19

\textbf{Introduction}

Coronavirus disease (COVID-19), caused by SARS-CoV-2, was first reported
in China at the end of 2019. The highly contagious virus quickly reached
pandemic proportions, and by the end of 2020, over 90 million COVID-19
cases had been reported in 218 countries.\textsuperscript{1}

Cameroon had its first registered SARS-CoV-2 positive test in early
March 2020.\textsuperscript{2,3} Cases started to rise rapidly
country-wide, and by March 17, 2020, Cameroon was under a strict public
health alert; wearing of masks became mandatory in all public areas and
education and awareness campaigns were implemented. Cameroon had the
highest absolute number of cases in the central Africa sub-region in
2020, with almost 30,000 reported cases and nearly 500
deaths\textsuperscript{4}. However, the true number of SARS-CoV-2
infections in Cameroon is unknown because of both the likely large
number of people with asymptomatic or mildly symptomatic infections, as
well as the lack of widespread testing.\textsuperscript{5} Thus,
determining the extent of community spread and establishing baseline
seroprevalence data are needed to better understand population immunity
levels and the impact of public health interventions, such as
vaccinations, on future waves of transmission.

The purpose of this study was to estimate and describe the prevalence of
SARS-CoV-2 antibodies among individuals aged \emph{\textgreater{}} 5
years in the 10 regional capitals of Cameroon. In addition, we aimed to
determine factors associated with seropositivity. Finally, we gauge
knowledge and attitudes towards COVID-19. To the best of our knowledge,
this was the first national SARS-CoV-2 serosurvey in Cameroon.

\textbf{Methods}

\emph{Survey Design and Population}

We designed a cross-sectional, age-stratified SARS-CoV-2
seroepidemiological survey in community-based sites across 10 regional
capitals of Cameroon, in line with the World Health Organization (WHO)
UNITY studies framework.\textsuperscript{13,} This survey took place
from October to December 2020 at 30 purposively selected community-based
sites (three in each regional capital), including marketplaces, bus
stops, and busy commercial intersections. High traffic venues were
chosen because they most likely had a broad representation of age
groups, sexes, and socioeconomic statuses. The sites were selected in
conjunction with local stakeholders {[}Cameroon Ministry of Health, U.S.
Centers for Disease Control and Prevention (CDC) in Cameroon{]}. For a
more representative sample of the regional population, we set regional
quotas for three broad age groups: 5-19 years, 20-49 years, and 50+
years (Appendix Table 1). The quotas were proportional to the regional
population based on census data (2020) for each of these age
groups.\textsuperscript{14}

Children \textless{} 5 years were excluded due to the difficulty in
obtaining blood from young children, especially in such public settings.
At each site, survey staff used banners and other promotional materials
and loudspeakers to announce the survey and attract attention to the
on-site survey tent. If participants were traveling in groups, only one
adult and one child (5 years and above) per household were eligible to
participate based on self-reported relationships. Data were collected at
each site for approximately three weeks, until quotas were met.

Prior to participation in the survey, written informed consent was
obtained from adults (aged \selectlanguage{english}[?]21 years as per Cameroon regulations) and
emancipated minors and from parents for participants aged \selectlanguage{english}[?]20 years.
Written informed assent was also obtained from participants aged 10-20
years. The survey was approved by the Cameroon National Research Ethics
Committee and Columbia University reviewed and designated it as public
health surveillance. The study was reviewed in accordance with the U.S.
CDC human research protection procedures and was determined as research.
However the CDC investigators did not interact with any individuals or
have access to identifiable data or specimens for research purposes.

\emph{Procedures}

Data were collected from October 19 to December 17, 2020. A
questionnaire was first administered to participants (or their
parent/guardian for those ages 5-14 years) using SurveyCTO on tablet. In
this survey, which was adapted from the UNITY survey template,
researchers collected information about sociodemographic factors; past
COVID-19 symptoms; potential COVID-19 exposures {[}known contact with a
laboratory-confirmed case, travel (domestic or international), and
health facility use{]}; co-morbid conditions and other risk factors;
history of health seeking behavior; and knowledge, attitudes, and
beliefs about COVID-19. To asses past COVID-19-like illnesses,
participants were asked whether, since the beginning of the COVID-19
pandemic in January 2020 (before the first reported case in Cameroon),
they had experienced any of the following symptoms per case definition
used in Cameroon: dry cough, shortness of breath, tiredness, fever,
muscle pain, diarrhea, headache, new loss of smell/taste, sore throat,
nausea/vomiting.

After completing the questionnaire, 5 mL of venous blood were collected
and placed in a cooler box with ice packs. After providing consent,
participants who decided they did not want to complete the questionnaire
were still allowed to provide their blood specimens. At the end of each
day, samples were transported to a local laboratory where, using the
plasma preparation tubes (PPTs), they were centrifuged to separate the
plasma and then immediately frozen at \selectlanguage{english}-20degC. The frozen PPTs were
transported under cold chain to the National Public Health Laboratory
(LNSP) at the end of each week. At LNSP, the separated plasma in each
PPT was pipetted into two 1 mL cryotubes (one cryotube for each assay)
and frozen at minus \selectlanguage{english}-80degC until testing was performed.

Given the expected low seroprevalence (\textless{}10\%) of SARS-CoV-2
antibodies in the Cameroon population at that time a parallel testing
algorithm was used to improve both the positive predictive value (PPV)
and negative predictive value (NPV). Two enzyme-linked immunosorbent
assays (ELISA) tests available at the time (2020) were selected based on
several factors: (1) sensitivity and specificity of available tests
{[}minimum 95\% sensitivity and 90\% specificity, in line with United
States Food and Drug Administration Emergency Use Authorizations (US FDA
EUA) validation requirements{]}, (2) the best overall PPV and NPV of the
testing algorithm using the FDA/CDC calculator on available tests on the
market at that time point, (3) availability of plasma as the specimen
type for testing, (4) authorization for use by US FDA EUA, WHO emergency
use listing, CDC, or other internationally recognized bodies, and (5)
test availability for purchase and shipment within a reasonable
timeframe to complete this survey. The tests chosen were the Abbott
Architect SARS-CoV-2 IgG (Abbott Diagnostics, Illinois, United States;
100\% sensitivity and 99.6\% specificity based on FDA report) and the
WANTAI SARS-CoV-2 Ab ELISA (Beijing, China; 94.5\% sensitivity and 100\%
specificity according to manufacturer's report). The WANTAI assay
detects total antibody to the receptor binding domain (RBD) of the
SARS-CoV-2 spike protein, including IgM, IgA, and IgG antibodies, while
the Abbott assay only detects IgG antibodies against the nucleocapsid
(N) protein. When used in combination, this testing algorithm
theoretically should produce an overall PPV of \textasciitilde{}100\%
based on a prevalence from 1-10\% according to the FDA PPV
calculator.\textsuperscript{15}

WANTAI ELISA testing was performed at the LNSP while the Abbott
Architect assay was performed at the Blood Bank of Yaounde Central
Hospital because of the availability of appropriate equipment. Each
assay and test interpretation was performed according to the
manufacturer's instructions and included appropriate quality controls to
validate each run.\textsuperscript{16,17} After the testing was
completed in the laboratory, remnant plasma specimens were returned to
the -80degC freezers for long-term storage.

A call center with set operational hours was established to return the
results, which was listed on the consent forms provided to the
participants. Survey participants would call and obtain their test
results using a random identification number assigned at enrollment.

\emph{Statistical analysis}

For the analysis, only those who tested positive on both WANTAI and
Abbott assays were classified as SARS-CoV-2 antibody positive (Figure
1). Those who tested negative on only one or both assays were classified
as negative.

Sampling weights were calculated based on selection probabilities at
each site. Non-response weights (for questionnaire and each laboratory
test) were calculated at the individual level. Weights were calibrated
to regional population estimates by age and sex, and then normalized to
the total sample size.\textsuperscript{14} Weighting was carried out in
R using the glm, anesrake, and survey packages.

Seroprevalence estimation was done in SAS using the SURVEYFREQ procedure
and the calibrated survey weights. Taylor series variance estimation was
used to account for the clustered sample design, treating each survey
site as a separate cluster. Unweighted counts and proportions were also
computed in SAS. The \selectlanguage{greek}χ\selectlanguage{english}\textsuperscript{2} test was used to assess the
differences in prevalence across demographic characteristics.

We conducted unadjusted and multivariable logistic regression,
incorporating survey weights, to assess the associations between
demographic and behavioral characteristics with seropositivity. The
analysis included participants with complete age and sex data. Final
multivariable models included variables with p\textless{}0.05 and
variables (sex, age, residence, region, number of household members,
comorbid conditions, and history of COVID-19, travel) chosen \emph{a
priori} based on their likely association with the risk of SARS-CoV-2
past infection.

Regional-level seroprevalence estimates were applied to 2020
region-specific population projections from the Cameroon Statistics
Agency to estimate the total number of SARS-CoV-2 infections in each
region that had occurred in the survey period (October-December 2020).
These numbers were compared with the total number of reported cases in
the country at the end of the study (December 2020) to estimate the
ratio of reported cases to total SARS-CoV-2 infections.

Agreement in test results between the WANTAI and Abbott assays was also
evaluated using kappa statistics.

\emph{Role of the funding source}

The funder of the study was involved in the study design, data analysis,
data interpretation, and writing of the manuscript.

\emph{Results}

Overall, 10,386 individuals were enrolled in the survey. Of these, 9,180
(88.7\%) completed an interview, 10,071 (97.0\%) completed a blood draw,
and 9,686 (93.3\% of 10,071) had results from both antibody assays. In
total of 9,332 (89.9\% of 10,386) participants who had valid results
from both assays as well as valid age and sex data were included in the
analysis (Appendix Figure 1). From both assays, 4,738 (50.8\%)
participants tested negative, 1,023 (10.9\%) tested positive, and 3,571
had discordant results resulting in a concordance of 61.7\% and a kappa
of 0.19 (Appendix Table 2). The WANTAI assay produced more positive
results than the Abbott assay (4,280 (45.8\%) vs. 1,337 (14.3\%)).

Approximately half of the participants were female (51.2\%, or 3,548)
and were age 15-25 years (48.8\% or 4,529). All participants who
enrolled were Cameroonians, and the majority had completed secondary
education (43.1\%) (Table 1). Only 9.2\% of participants reported
co-morbid medical conditions (Table 1). Almost half of the participants
age [?]15 years (43.7\% or 3,351 of 8,399) reported being unemployed. The
majority of those who were employed, worked in the informal trade sector
(17.0\%) (Table 1).

The overall weighted and adjusted seroprevalence of SARS-CoV-2 among
those aged 5+ years across the 10 regional capitals of Cameroon was
10.5\% (95\% confidence interval {[}CI{]}: 9.1\%-12.0\%) among
participants [?]5 years (Table 2). The seroprevalence was higher among
males than it was among females {[}13.1\% (95\% CI: 11.5\%-14.9\%) vs.
8.0\% (95\% CI: 6.8\%---9.3\%); p\textless{}0.0001). Seroprevalence also
differed by location (p=0.0062), ranging from 7.5\% (95\% CI:
5.9\%-9.5\%) in the East region to 12.4\% in the Far North (95\% CI:
10.4\%-14.8\%) and North West (95\% CI: 10.5-14.7) regions. Across age
groups, seroprevalence ranged from 7.9\% (95\% CI: 5.9\%-10.7\%) among
participants 5-14 years, to 19.2\% (95\% CI: 14.7\%-24.8\%) among those
aged 60 years and above. Among those who reported a comorbidity at the
time of testing, 15.8\% (95\% CI: 12.8\%-19.4\%) were seropositive.
Further, among participants who were diabetic at the time of testing,
24.2\% (95\% CI: 15-4\%-36.0\%) tested positive for SARS-CoV-2
antibodies. Among participants who had reported recent travel, 15.9\%
(95\% CI:11.6\%-21.5\%) of those who had reported recent international
travel were seropositive and 11.9\% (95\% CI:10.6\%-13.4\%) of
participants who had reported recent domestic travel were seropositive
(Table 2).

In the multivariable analysis females had a significantly lower
seroprevalence than males (adjusted odds ratio {[}aOR{]}: 0.61, 95\% CI:
0.51-0.74). Further, participants residing in the North (OR: 0.54
{[}95\% CI: 0.30-0.99{]}, Adamawa (aOR: 0.62 {[}95\% CI: 0.41-0.94{]}),
the East (aOR: 0.57 {[}95\% CI: 0.40-0.82{]}), and Littoral (aOR: 0.60
{[}95\% CI: 0.40-0.88{]}) regions had a lower seroprevalence compared to
those in the South West (Table 2). The odds of having tested positive
for this virus were also significantly higher across older age groups
(as compared to children ages 5-14 years); (aOR: 1.15 {[}95\% CI:
0.12-10.76), for those ages 15-25 years and aOR: 1.72 {[}95\% CI:
0.21-14.25) for persons aged 26-35 years). Seroprevalence was higher
among participants who reported having ever tested SARS CoV-2 positive
(aOR: 3.61 {[}95\% CI:2.01-6.47{]}), and among participants who traveled
internationally in the past year compared to those who did not travel at
all within the past year (aOR: 1.56 {[}95\% CI: 1.10-2.22{]}). In
multivariable analyses, seroprevalence did not differ by residential
setting (urban vs. rural), history of comorbidities, or household size.

Based on the seroprevalence results from the study, we estimated that
over 2 million persons were seropositive for SARS-CoV-2 (cumulatively)
in the 10 regional capitals of Cameroon during October to December 2020,
as compared to 21,160 cases officially reported at that time (Table
3).\textsuperscript{18} We estimate that one laboratory-confirmed case
was reported for every 110 SARS-CoV-2 infections across the 10 regional
capitals. The highest number of SARS-CoV-2 infections was estimated to
be in Center region with an estimated 475,000 infections, and the lowest
number in Adamawa with an estimated 64,700 infections.

\textbf{Discussion}

Overall, we found that an estimated 10.5\% of Cameroonian survey
participants aged [?]5 years were SARS-CoV-2 seropositive at the end of
2020. SARS-CoV-2 seroprevalence ranged widely by region (7.5\% to
12.4\%) and seroprevalence was higher among males, persons older than 25
years of age, those who reported ever having tested positive for
SARS-CoV-2 and among those who had reported having a recently traveled.
However, seroprevalence did not differ by, residential setting (urban
vs. rural), having a comorbid condition, or household
size.\textsuperscript{19} Another seroprevalence survey conducted in
Cameroon that sampled households in Yaound\selectlanguage{ngerman}é, Cameroon that was conducted
around the same time as this study found a seroprevalence of 29.2\%
(95\% CI 24·3--34·1).\textsuperscript{20} This was more than 2.5 times
higher than what we found for the seroprevalence (11.8\%) in the Center
region where Yaoundé is located. Like our survey, this survey also found
that seroprevalence was higher among males. However, unlike our survey,
they found a higher seroprevalence among participants living in larger
households.

Our finding of 10.5\% seroprevalence translates to an estimated
2,347,500 total infections across Cameroon at the time of the survey.
This is over 100 times higher than the cumulative number of cases
reported as of December 30, 2020.\textsuperscript{18} Currently, there
are 124,392 all time confirmed cases and 1,965 deaths reported in
Cameroon due to SARs-CoV-2\textsuperscript{40}. A meta-analysis that
used data from seroprevalence studies conducted in 2020 found an overall
seroprevalence of 19.5\% in Sub-Saharan Africa which varied widely and
was significantly higher than that in high-income
countries.\textsuperscript{21} The authors also found that
seroprevalence estimates were a median 18.1 times higher than the
cumulative incidence of reported cases overall and 600 times higher in
Sub-Saharan Africa. Another meta-analysis which used data published
through December 2021 from Africa only (including data from our survey)
also found a very high ratio (97:1) of seroprevalence to cumulative
incidence that remained fairly constant over time. Several reasons have
been suggested for the seemingly low number of cases and even lower
mortality rate and the misalignment between seroprevalence findings and
reported cases in Africa. These factors include lack of access to health
services, including SARS-CoV-2 testing; limited public health
surveillance capacity and infrastructure, including shortages of
SARS-CoV-2 real-time (RT)-PCR test kits and other laboratory supplies; ;
swift and wide-reaching public health measures established by many
countries; and the overall lower age of its
population.\textsuperscript{23-24} Further, in 2020, the stigma
associated with COVID-19, along with misinformation and disinformation
in the community likely resulted in testing avoidance which exacerbated
the undercounting of cases.\textsuperscript{25}

As SARS-CoV-2 can spread asymptomatically, the official reported number
of cases to health reporting systems globally did not include all the
possible infections. This underscored the need for seroprevalence
surveys that could present a full picture of the disease burden in a
population by measuring SARS-CoV-2 antibodies in sampled blood specimens
to detect previous infection, regardless of the presence or absence of
symptoms. In countries where testing numbers were low, both because of
low demand and testing supply shortages, the need for serosurveys was
critical to understanding the epidemic both on a national and
sub-national level, which was the case for Cameroon. Thus, we designed
the first SARS-CoV-2 seroprevalence survey that included all 10 regions
of Cameroon comprising over 10,000 adults and children aged \selectlanguage{english}[?]5 years. In
each city, individuals were recruited from multiple sites to increase
the diversity of participants. The survey also demonstrated the
feasibility of performing a community-based serological survey in large
African regional centers.

The prevalence estimates from this study were based on two assays:
WANTAI SARS-CoV-2 Ab ELISA and Abbott Architect SARS-CoV-2 IgG. The
WANTAI assay, which was made available by the WHO and was not
independently evaluated at the time of the survey while the Abbott assay
was authorized for use by the U.S. FDA after independently qualifying
the assay with 100\% sensitivity and 99.6\%
specificity.\textsuperscript{26} In 2020, many antibody test kits
entered the market with variable, and in some cases unreliable, test
performance characteristics (sensitivity, specificity, PPV and
NPV).\textsuperscript{27} To overcome some of these test kit performance
issues, we employed a parallel two-test algorithm which increased the
overall PPV for more accurate seroprevalence estimates. This approach
differed substantially from that used by the majority of serosurveys
conducted in the early days of the pandemic whereby a single test was
employed to estimate prevalence, leading to uneven surveillance data
quality.\textsuperscript{7,28} Some of these antibody tests included
lateral flow immunoassays that had poorer performance than ELISA
assays.\textsuperscript{29}

In our parallel two-test algorithm, we found poor concordance between
the WANTAI and Abbott assays (Kappa value = 0.19), with the WANTAI assay
producing a very high positivity rate of 45.9\% compared to that of the
Abbott assay, which was 14.3\%. Similar to our findings, other studies
have noted high positivity rates with the WANTAI assay compared to other
ELISA assays.\textsuperscript{30-32} One possible explanation for this
discrepancy is that the WANTAI assay detects total antibodies to the
receptor binding domain (RBD) of the SARS-CoV-2 spike protein while the
Abbott assay only detects IgG antibodies against the N protein. Assays
that detect total antibodies have been shown to be more sensitive than
those that detect either IgM or IgG and detect antibody earlier in
infections (\textless{}21 days post-symptom
onset).\textsuperscript{33-35} Another possible contribution to the high
positivity is the lower specificity due to cross-reactivity to other
circulating antibodies resulting from past infections from other
pathogens. This has been noted in other evaluations, including WHO's own
evaluation,\textsuperscript{36} resulting in false-positives and higher
overall prevalence estimates.\textsuperscript{37} Conversely, the lower
positivity rate from the Abbott assay may be due to the lower
sensitivity associated with only detecting IgG antibodies and timing of
testing from days post infection (\textless{}21 days). Given the
shortcomings of both assays, as well as the unknown prevalence of
COVID-19 in Cameroon at the time of the survey, a parallel testing
algorithm was used to reduce false positives and improve the overall PPV
of the SARS-CoV-2 prevalence estimates for this survey.

This survey had several limitations. First, the use of convenience
sampling from the regional capitals may indicate that the results are
not representative of the entire population of Cameroon. However, the
use of age stratified targets and post-stratification with the
participant weights was used to help reduce the effects of this
selection bias. Second, bias may have been introduced because of
experiences with COVID-19, for example, people may have been more
willing to participate if they or someone they know had been affected by
COVID-19, or they may have been less willing, if they felt like they had
already contracted COVID-19 and were not interested in finding out their
antibody statuses. Third, the assays could have missed individuals who
were still in the early stages of seroconversion. Our survey also has
several strengths. It was the first SARS-CoV-2 seroprevalence survey
that included all 10 regions of Cameroon and included over 10,000 adults
and children aged \selectlanguage{english}[?]5 years. In each city, individuals were recruited
from multiple sites to increase the diversity of participants. The
survey also demonstrated the feasibility of performing a community-based
serological survey in large African urban centers. Further, we used two
antibody tests to increase both PPV and NPV.

We conducted our survey in late 2020 before Cameroon experienced its
second largest SARS-CoV-2 wave and two subsequent waves that likely
increased seroprevalence,\textsuperscript{18} especially given that only
3\% of the population had been vaccinated by the end of that
year.\textsuperscript{38} Repeated seroprevalence surveys after each
large infection wave would have been useful to understand how readily
the virus spreads in this population, and also the impact of vaccines on
the spread of the virus and any associated mortality.

\textbf{Conclusion}

Approximately one in ten individuals in the regional capitals of
Cameroon had been infected with SARS-CoV-2 by December 2020, indicating
extensive and under-reported circulation of SARS-CoV-2 in the country,
with almost 100-fold more cases across Cameroon as compared to the
number of cases reported to the WHO. This finding highlights the
importance of conducting seroprevalence surveys especially in places
where access to testing may be limited and repeating such surveys as
part of tracking the trajectory of the pandemic.

Seroprevalence surveys, if conducted using accurate testing algorithms,
can capture a fuller burden of infection in a population, allowing
public health officials to decide on an effective pandemic response and
identify subgroups at higher risk for infection. With the availability
of home-testing and more mild disease, reported numbers of infections
will become less reliable and national seroprevalence surveys will
become more important to understand disease burden and geographical
impacts on a population.

\textbf{Hosted file}

\verb`Appendix_and_Tables_Figures_clean.docx`  available at \url{https://authorea.com/users/614546/articles/641347-seroprevalence-of-sars-cov-2-in-10-regional-capitals-of-cameroon-october-december-2020}

\selectlanguage{english}
\FloatBarrier
\end{document}

