key: cord-1038681-xxh3i8h5
authors: Quashie, P. K.; Mutungi, J. K.; Dzabeng, F.; Oduro-Mensah, D.; Opurum, P. C.; Tapela, K.; Udoakang, A. J.; WACCBIP COVID-19 Team,; Asante, I.; Paemka, L.; Kumi-Ansah, F.; Quaye, O.; Amoako, E.; Armah, R.; Kilba, C.; Boateng, N. A.; Ofori, M. F.; Kyei, G. B.; Bediako, Y.; Ndam, N. T.; Abugri, J.; Ansah, P.; Ampofo, W. K.; Mutapi, F.; Awandare, G. A.
title: Trends of SARS-CoV-2 antibody prevalence in selected regions across Ghana
date: 2021-04-28
journal: nan
DOI: 10.1101/2021.04.25.21256067
sha: a5674948b3975d0fd338675fab7ce437c478a8ff
doc_id: 1038681
cord_uid: xxh3i8h5

To estimate the level of community exposure to SARS-CoV-2 in Ghana, we conducted phased seroprevalence studies of 2729 participants in selected locations across Ghana. Phase I screening (August 2020) covered a total of 1305 individuals screened at major markets/lorry stations, major shopping malls, hospitals and research institutions involved in COVID-19 work. The screening was performed using a strip-in-cassette lateral flow type Rapid Diagnostic Test (RDT) kit that simultaneously and separately detected IgM and IgG antibodies against SARS-CoV-2 nucleocapsid protein. In Phase I, 252/1305 (19%) tested positive for IgM or IgG or both. Exposure rate was significantly higher among individuals tested at markets/lorry stations (26.9%) compared to those at Shopping Malls (9.4%). The 41--60-years age group had the highest exposure rate (27.2%). People with only a basic level or no formal education had a higher exposure rate (26.2%) than those with tertiary level education (13.1%); and higher in informally employed workers (24.0%) than those in the formal sector (15.0%). Phases II and III screening activities in October and December 2020, respectively, showed no evidence of increased seroprevalence, indicating either a reduced transmission rate or loss of antibody expression in a subset of the participants. The Upper East region has the lowest exposure rate, with only 4 of 200 participants (2%) seropositivity. Phase IV screening in February 2021 showed that exposure rates in the upper income earners (26.2%) had almost doubled since August 2020, reflective of Ghana's second wave of symptomatic COVID-19 cases, which began in December 2020. The Phase IV results suggest that seroprevalence levels have become so high that the initial socioeconomic stratification of exposure has been lost. Overall, the data indicates a much higher COVID-19 seroprevalence in the Greater Accra Region than was officially acknowledged, likely implying a considerably lower case fatality rate than the current national figure of 0.84%. Additionally, the high exposure levels seen in the communities suggest that COVID-19 in Ghana still predominantly presents with none-to-mild symptoms. Our results lay the foundation for more extensive SARS-CoV-2 surveillance in Ghana and the West African sub-region, including deploying rapid antigen test kits in concert to determine the actual infection burden since antibody development lags infection.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported in Wuhan, China, in late 2019 [1] . By April 20 th 2021 there were 141,058,320 COVID-19 SARS-CoV-2 reported infections with 3,015,314 associated deaths (case fatality ratio (CFR): of 2.1%) globally. Of these, 4,437,846 COVID-19 cases and 118,133 deaths (CFR: 2.7%), representing 3.07% and 3.85% of all reported global cases and deaths, were from the 55 African Union Member States [2] . Ghana, from the first two reported (imported) cases on March 12 th 2020, by April 16 th 2021 reported a cumulative total of 91,709 confirmed cases with 771 associated deaths (CFR of 0.84%) by this date [3] .

The current gold standard method for diagnosis of SARS-CoV-2 infection is by real-time reverse transcription polymerase chain reaction (RT-PCR), which detects viral nucleic acid sequences, and thus the virus, present in the upper respiratory tract (nasopharyngeal or oropharyngeal) swab samples [4] [5] [6] . Due to limited resources, tests are prioritised on symptomatic, severe, and/or suspected cases, and occasionally on contacts of confirmed cases. Common symptoms of SARS-CoV-2 infection include fever, dry cough, tiredness and other variable ones with onset between 5 to 14 days after infection [7] . Approximately 80% of infected persons show mild or no symptom [8] , however, posing a danger of unmitigated transmission and potential rapid rise in disease onset, severity and death [9] . Additionally, RT-PCR sensitivity may be affected by viral load, virus replication rate, RNA isolation method, and the source or timing of swab collection relative to disease stage [10] . This could lead to false negativity of about 20% [11] , indicating that actual infections may be higher than reported per test.

Rapid immunodiagnostic tests (RDTs) can be used to detect either SARS-CoV-2-expressed proteins (antigens) in respiratory tract samples (e.g., sputum, throat swab) or human anti-SARS-CoV-2 specific antibodies in blood or serum within minutes. Rapid antigen tests have utility for rapid detection of transmissible infections but have lower sensitivity than PCRbased methods [12] and have become common for routine SARS-CoV-2 screening at ports of entry. Some RDTs also detect the presence of antibodies against SARS-CoV-2 in bodily fluids. These are useful for performing population level surveillance of viral exposure. Unlike antigen RDT's which pick up active and often transmissible infection, antibody RDTs tend to pick up the evidence of previous or recent infection and cannot be used to detect active infection [12] . There are more than 280 Conformité Européenne-in vitro diagnostics (CE-IVD)-marked COVID-19 antibody detection RDT kits listed with the Foundation for Innovative Diagnostics (FIND) [13] . Currently, lateral flow immunoassays (LFIAs), chemiluminescence immunoassays (CLIAs), or enzyme-linked immunosorbent assays (ELISAs) are commonly . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted April 28, 2021. ;  used for detection of SARS-CoV-2 IgM and IgG antibodies [14, 15] . Similar to other infections, SARS-CoV-2 elicits an immune response [16] , and the presence of the virusspecific antibodies in blood indicates previous or current infection regardless of the presence or absence of symptoms [17, 18] . Generally, IgM or IgG are produced early and later in infection, respectively [19] . It is currently unknown how long SARS-CoV-2 IgM and IgG antibodies persist, however, seroconversion of IgM appears to peak simultaneously with IgG within 2 to 3 weeks after symptoms onset [10, 17, [20] [21] [22] [23] [24] In addition to retrospectively evaluating infection dynamics and the population disease burden, serology tests are useful for vaccine trials, therapeutic antibodies results analyses, and tests for individual and herd immunity. Antibody presence can also help identify COVID-19-recovered individuals and potential donors of convalescent plasma for immunotherapy of critically sick COVID-19 patients [25] . Some seroprevalence studies have used crosssectional snapshots to evaluate community level exposure of SARS-CoV-2 [26] but to our knowledge, no single study has attempted to track the spatial-temporal dynamics of SARS-CoV-2 exposure in Africa. Ghana reported its first two (imported) cases on March 12 th , 2020 [3] . By April 4 th , positive cases who had neither travel history nor known contact with confirmed cases, were detected, implying local transmission. To estimate COVID-19 community spread in Ghana, over a 7-month period, we randomly screened for IgM and IgG antibodies against SARS-CoV-2 in people at various public places in Accra (National capital, where >50% of reported cases occur), Kasoa (a densely-populated town in the Central Region, and a COVID-19 transmission hotspot [27] and which shares a border with Accra), Cape Coast (Central Regional capital), Akropong (a small town in the Eastern Region, a 15minute drive away from Accra), Navrongo (a small town in the Upper East Region, which hosts a public university and a government Health Research Centre) and Bolgatanga (the Upper East Regional capital) (Figure 1) . A questionnaire administered during the study collected demographic data as well and evaluated the COVID-19 knowledge, attitudes and perceptions (KAP) of study participants.

This study was a multi-site repeated observational cross-sectional study carried out over a period of 7 months from July 27, 2020 to February 26, 2021. Phase I was performed between 27 July and September 14, 2020 (designated August 2020), followed by additional phases in October 2020, December 2020 and February 2021 to identify changes from the initial rates observed at public places ( Figure S1 ). For ease of reference in the text, and for site anonymity, the sites were assigned codes based on site type and risk factors: markets and lorry stations (ML), malls (M), research centres (R), hospitals (H) and generalised community screening (C). Generalised community screening included attendees at a concert since that reflected individuals who would be otherwise dispersed through the community. A research centre involved in mass COVID-19 testing and a COVID-19 treatment centre were given the respective codes, RC and HC. Phase I participants were invited to volunteer for the study at two shopping malls, three major markets/lorry stations (ML1-3), two research institutes involved in COVID-19 work (R1) and COVID-19 testing (RC), and three major hospitals, one of which was a COVID-19 treatment centre (H1, H2, and HC). Informed consent was obtained from all study participants. Exposure to COVID-19 was detected using a strip-in-cassette lateral flow rapid diagnostic test kit which simultaneously detects IgM and IgG antibodies against SARS-CoV-2 antigens. Phase II screened participants at one market (ML4), one research centre (R1) and two hospitals (H1, H4) while Phase III screened participants at ML1 and across two towns in the Upper East Region (C1). During Phase IV, the exposure levels of upper-income earners were evaluated by screening at 2 malls (M1 and M3) and a repeat screening at H2. In addition, the exposure level in a small town (C3) in the Eastern Region, near Accra, was estimated. Screening at hospitals and research facilities included only staff members and their close contacts; patients at the hospitals were excluded from this study. All tests were performed on-site and participants were subsequently informed of their exposure status and counselled to adhere to COVID-19 mitigation protocols. When IgM was detected, participants were referred for a COVID-19 PCR test.

The 'UNSCIENCE COVID-19 IgG/IgM antibody Rapid Test Kit' (Catalogue# UNCOV-40, Lot Number 20200326) was registered with the Ghana FDA, and the kit validation report was submitted to the Ghana Food and Drug Authority (FDA). For the validation exercise, sera from RT-PCR confirmed COVID-19 cases were used to evaluate several kits' performance since there were no established SARS-CoV-2 antibody detection standards for use at the commencement of this study. This kit had a manufacturer-declared IgG sensitivity and . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

The copyright holder for this preprint this version posted April 28, 2021. ;  specificity of over 98% (https://covid-19-diagnostics.jrc.ec.europa.eu/devices/detail/634).

Using the Ghana Food and Drugs Authority (FDA) validation protocol 36 , the UNSCIENCE kit demonstrated a sensitivity of 66% when tested using 100 Ghanaian convalescent COVID-19 patient sera (2-4 weeks after a PCR-positive result). We checked the existence of preexisting cross-reactive antibodies using sera from 100 PCR-verified COVID-19 negative samples and obtained a specificity of 94%. In the validation exercises, when a test result was not obvious, at least 3 researchers validated the reading. In the rare case of an invalid test (no control line, or wrong location of bands), the test was repeated. A representative set of randomly chosen positive and negative test results are shown in Figure S2 . The kit was also adjudged to have a concordance of 72% with the WHO-recommended Wantai ELISA kit (https://www.fda.gov/media/140929/download).

A short questionnaire was administered to capture participant demographic data, knowledge of COVID-19 and COVID-19 testing history. The data, including the antibody test results were entered and managed using Research Electronic Data Capture suite (REDCap) [28] .

The data were cleaned by checking for completeness, duplication and consistency. Cleaned data were analyzed with Stata 16 (StataCorp, College Station, Texas, USA) and R/RStudio [29, 30] . GraphPad Prism version 8.0.0 [31] was used for some additional analysis and generation of figures. Descriptive analyses were performed and univariate and multivariate logistic regression models were used to assess the association between seroprevalence and risk factors. Multivariable logistic models for seropositivity were obtained by using a backward stepwise procedure. Demographic variables that were associated with seropositivity at the P<0.25 level were included. The overall goodness of fit was assessed using the Wald statistic. Unadjusted and adjusted odds ratios with 95% confidence intervals were computed and presented as parallel dot plots with error bars. Statistical significance was inferred for p-values below 0.05.

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A total of 2729 participants were screened for this study ( Figure (Table 1) . There was a slightly higher number of female participants than males. The modal age range was 21-40 years, and over 40% of the participants had a tertiary education. Tertiary education was defined as having a post-secondary qualification such as a diploma, degree or above. Most respondents worked in the informal sector, with low or mid-level socioeconomic status. Over 90% of participants had good knowledge of COVID-19 symptoms, transmission routes and preventative measures ( Figure S3 ). Such knowledge did not, however, correlate with participants' seropositivity status or maskwearing prior to recruitment. Only 7% of participants had previously received a COVID-19 PCR test ( Figure S4 ). Similar participant characteristics were observed in Phases II, III and IV with smaller numbers of participants.

In Phase I, SARS-CoV-2 IgG, IgM or both antibodies were detected in 19% of all participants ( Figure 2A) , with the highest rate amongst participants sampled in markets/lorry stations (27%). Among health workers, those at COVID-19 treatment/testing sites had higher exposure rates compared to their colleagues who were not directly handling COVID-19 patients or samples. There was no significant difference in seropositivity across genders ( Figure 2B ). When stratified by age categories, the highest level of seroprevalence (27.1%) was observed in the 41-60 years age group ( Figure 2C ). Participants with higher educational backgrounds ( Figure 2D ), those employed in the formal sector ( Figure 2E ) and those with higher economic standing ( Figure 2F ) had lower exposure levels than participants with lower educational background, informal sector workers and poor economic background.

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The copyright holder for this preprint this version posted April 28, 2021. ;  Only 20.9% of seropositive participants reported having had COVID-19-like symptoms ( Figure 3 ).

Logistic regression analysis was performed on data from Phase I to identify factors that correlated with increased risk of SARS-CoV-2 exposure ( Figure 4 ). Univariate modelling showed that socio-demographic factors were significantly associated with increased or decreased exposure. These were: being sampled at either markets and lorry stations (Odds ratio, OR:3.6, 95% confidence interval, CI: 2.4-5.4) or a COVID-19 treatment/testing centre were not statistically significant (Table 2, Figure 4 ).

As follow-ups to Phase I, the trend of population seroprevalence was again investigated in Phase II and III. Two months after the initial public places screening (October, 2020), 144 individuals were screened at a lorry station in Accra and 212 participants at two hospitals in Accra and Cape Coast. Overall, seroprevalence at the lorry station was 19.7%, and 13% at the two hospitals. The H4 facility staff had higher (18.5%) seroprevalence level than those at H1, previously sampled in Phase I. A Phase III screening exercise was conducted at M1, which was originally sampled in Phase I, and that showed an estimated seroprevalence of (Table 1) . Individuals screened at the Afrochella concert (C2) showed an estimated seroprevalence of 16%, which was similar to the Phase I data, with the HC site excluded.

Phase IV: Impact of the second wave . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted April 28, 2021. ;  Beginning in late December 2020, large numbers of symptomatic COVID-19 cases started to be detected at hospitals and treatment centres in Accra and other major cities. The patients were mostly of high socio-economic standing [32] . We therefore performed repeat screening at M1 and H2 (both sampled in Phase I) and sampled again at M3 and a small town in the Eastern Region (C3). The average seroprevalence at the two malls (M1 and M3) was at 27%, whilst H1 and C3 recorded 25% and 17% respectively.

This study was necessitated by a dearth of epidemiological data on COVID-19 prevalence in Ghana. In the first few months of the pandemic when prevalence was low, Ghana ranked high among African countries, and even globally, for administering high numbers of tests per million people [33] . To meet the high demand for testing, Ghana's main testing centre, Noguchi Memorial Institute for Medical Research, employed "sample pooling" methods [34] [35] [36] [37] . However, since then, Ghana has declined significantly to number 22 in tests per million of population in Africa [38] . Data from the Ghana Health Service's COVID-19 archives [3] indicates that testing has significantly reduced after peaking in June, correlating with a drop in daily reported cases. Among other factors, the reduced testing could be due to the fact that at the current positivity rate of 8.3% of tested cases, sample pooling is no longer a viable cost-cutting and test-rate enhancing measure. The seroprevalence rate average of 19.3% obtained from our public screening exercises is probably a better reflection of SARS-CoV-2 infections in Ghana, especially in the large and densely populated urban areas.

Additionally, currently, most RT-PCR tests in the country are administered to travellers, representing a higher economic tier of society. The relatively low (9.3%) seroprevalence initially observed in malls, assumed to be frequented by the higher tiers of society, may correlate well with the official 10% RT-PCR test positivity rate reported in September 2020 [3] .

Participants across all sites demonstrated good knowledge of COVID-19 risks, symptoms and preventive measures. This did not however translate into observation of protocols in the markets and lorry stations, where, by visual estimation, 10-50% of the study participants arrived mask-less and had to be requested to wear a mask donated by the study. This attitude corresponds with two surveys on mask-wearing, carried out by the Ghana Health Service which showed public mask wearing of ~40% and 10% in July and September, respectively [39, 40] . Our previous genomic study showed evidence of undetected community spread likely caused by asymptomatic individuals [27] . Of note, nearly 80% of people who were seropositive did not report significant COVID-19 symptoms (Figure 3 ), confirming that SARS-CoV-2 infections in Ghana are predominantly asymptomatic, . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted April 28, 2021. ;  consistent with reported global trends [8] . With the 19.3% seroprevalence in the Greater Accra Region (GAR), we inferred that nearly 1 million out of the estimated 5 million GAR residents may have already been exposed to SARS-CoV-2. This staggering number suggests that the actual fatality rate of COVID-19 in Ghana may be much lower than the reported CFR of 0.7%, since that would have translated to approximately 7000 deaths in a large metropolis like Accra, which would have been rather very obvious . Additionally, there was no evidence of a stressed or panicked healthcare system nor visible or anecdotal evidence of excess deaths during the Phase I hospital screening.

Given the higher-than-expected seroprevalence observed in the Greater Accra Region, Our observed seropositivity rates are in line with previous reports from other African countries [41, 42] . A study in Kenya estimated 20% SARS-CoV-2 seropositivity in adults (~1.6 million people) at a time when the total reported infections were 2093 (with approximately 90% asymptomatic cases) and 71 deaths of all ages [43] . The initial trend relating income disparity and COVID-19 seropositivity is not surprising. Even in countries where lower seroprevalence was reported, such as China (1.63%), lower income status correlated with the highest seroprevalence (5.62%) [44] , and this trend was initially reflected in this current study. The shift to high prevalence even in high socioeconomic brackets is . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted April 28, 2021. ;  likely due to poor adherence to COVID-19 protocols during the period of this study, likely due to election activities [45] and the 2020 Christmas/2021 New Year holiday festivities.

By surveying participants at different sites and times, representing categories of different perceived risk factors, this study obtained credible estimates for population-level prevalence across these sites and how that changed over the sampling period. This will allow future screening at these sites to determine the seroprevalence trends. However, most seroprevalence studies only reflect past disease burden. Using Markets and Lorry Stations enabled sampling of a broad cross-section of the Ghanaian populace.

Phase I of the study was conducted in the region with the greatest burden of reported infections and it was expected that a country-wide survey would yield less seroprevalence.

Site H3, situated in the town of Cape Coast, a tourist hub and Central regional capital, exhibited a very high prevalence at 18.5% during Phase II, but this was not surprising given that M4, located in Kasoa, also in the Central Region, exhibited an exposure rate of 28% during Phase I. The low seroprevalence observed at C1 (2%) during Phase III hinted that community size/density may play a role in COVID-19 transmission. Given the geographical remoteness of C1 to the major hotspots of Accra and Kumasi, another small community (C3) in the country's Southern belt with higher population density was screened, yielding an observed prevalence rate of 17%, and showing that SARS-CoV-2 exposure is not just a metropolitan burden, but one that needs to be tracked across the country. This, however, does not rule out that towns with lower population densities and who are far from metropolitan areas may exhibit lower seroprevalence levels.

During validation, this kit showed a sensitivity of 66%, when compared to PCR positivity. This is despite the manufacturer recoding sensitivity and specificity values above 98%. The apparent low sensitivity observed in local validation may just be reflective of low level antibody expression levels in the patient sera from early Ghanaian cases. The import of this is that the seroprevalence levels reported in this study are likely underestimates of true prevalence.

One oft-repeated concern with SARS-CoV-2 seroprevalence studies in Africa is crossreactivity due to pre-existing antibodies to other viruses and vaccines [46] . Some studies have reported extensive cross-reactivity against SARS-CoV-2 in Africa [47] ). However, most of these studies are severely flawed, and as such their conclusions are unreliable. These flaws include extremely small study sizes (below 500 and even sometimes below 100) [48] , tend to be based at single institutions and/or cities [47] and use samples collected at widely . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted April 28, 2021. ;  divergent time periods for their 'Western' and 'African' pre-COVID-19 samples [48] . The UNSCIENCE COVID-19 IgG/IgM antibody Rapid Test Kit used in our study exhibited 94% specificity during validation (with plasma from 100 COVID-19 PCR-negative individuals).

Antibody RDTs are contraindicated in cases of active fever, based on manufacturer's information leaflets, unpublished analyses and other studies [47] . We confirmed that none of the study respondents had temperature above 38, thereby reducing the likelihood of fever affecting the results.

Antibody cross-reactivity with other pathogens is often manifested in IgM detection [49, 50] .

During validation, and in the field, detection of IgM was uncommon, and when detected, IgM was often accompanied by IgG. This reduced the likelihood that those IgM detections were as a result of cross-reactivity. That said, a cross-reactivity rate of 6% with IgM was detected during validation. However, the test kit performed even better in the field; Navrongo and Bolgatanga in the Upper-East region of Ghana are towns with populations highly vaccinated against other pathogens, yet only 2% of 200 individuals (4 individuals) showed seropositivity in this study. This low seropositivity corelated well with the low level of reported COVID-19 in those towns at the time and hinted that the rates observed in Accra and environs were due to the SARS-CoV-2 exposure rate, but not from cross-reactivity. Taken together, there is a low likelihood that cross-reactive antibodies played a significant role in this study.

This study highlights a relatively high level of SARS-CoV-2 infections in the Greater Accra, Finally, resources should be mobilised to research the molecular and immunological mechanisms underlying the apparent high tolerance to COVID-19 observed in Ghana, the West African sub-region, and Africa as a whole.

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The copyright holder for this preprint this version posted April 28, 2021. ;

Procedures in this study conform with the Ghanaian Public Health Act, 2012 (Act 851) and the Data Protection Act, 2012 (Act 843). Ethical approval was received from the Ethics Board of the College of Basic and Applied Sciences, University of Ghana (ECBAS 063/ [19] [20] , and the Ethical Review Committee of the Ghana Health Service (GHS-ERC 011/03/20).

In line with the ethical protocol above, written informed consent was obtained for all study participants. Upon consent, each participant was assigned a unique identification number (ID). This ID was used for testing and data recording, thereby delinking participant identification with the test results and questionnaire answers. All consent forms are kept in a locked cabinet accessible to only the study PI and the WACCBIP Data Manager. 

We are sincerely grateful to all study participants for their contributions. We also thank the leadership of the various malls, markets, medical and research centres who allowed screening on their premises. We are grateful to the WACCBIP staff, especially the public engagement team, for their assistance in planning the screenings at the study sites.

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The copyright holder for this preprint this version posted April 28, 2021. ;  This study was funded by a Wellcome/African Academy of Sciences Developing Excellence 

None to declare . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted April 28, 2021. ; .

It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint .

It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted April 28, 2021. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

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The copyright holder for this preprint this version posted April 28, 2021. ; Akropong (C3) . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

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The copyright holder for this preprint this version posted April 28, 2021. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted April 28, 2021. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

The copyright holder for this preprint this version posted April 28, 2021. ;

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