High rates of SARS-CoV-2 infection in pregnant Ugandan women and association with stunting in infancy (preprint)

Background: SARS-CoV-2 has been well studied in resource-rich areas but many questions remain about effects of infection in African populations, particularly in vulnerable groups such as pregnant women. Methods: We describe SARS-CoV-2 immunoglobulin (Ig) G and IgM antibody responses and clinical outcomes in mother-infant dyads enrolled in malaria chemoprevention trials in Uganda. Results: From December 2020 to February 2022, among 400 unvaccinated pregnant women, serologic assessments revealed that 128 (32%) were seronegative for anti-SARS-CoV-2 IgG and IgM at enrollment and delivery, 80 (20%) were infected either prior to or early in pregnancy, and 192 (48%) were infected or re-infected with SARS-CoV-2 during pregnancy. We observed preferential binding of plasma IgG to Wuhan-Hu-1-like antigens in individuals seroconverting up to early 2021, and to Delta variant antigens in a subset of individuals in mid-2021. Breadth of IgG binding to all variants improved over time. No participants experienced severe respiratory illness during the study. SARS-CoV-2 infection in early pregnancy was associated with lower median length-for-age Z-score at age 3 months compared with no infection or late pregnancy infection (-1.54 versus -0.37 and -0.51, p=0.009). Conclusion: Pregnant Ugandan women experienced high levels of SARS-CoV-2 infection without severe respiratory illness. Variant-specific serology testing demonstrated evidence of antibody affinity maturation at the population level. Early gestational SARS-CoV-2 infection was associated with shorter stature in early infancy.

Reconstructing the SARS-CoV-2 epidemic in eastern Uganda through longitudinal serosurveillance in a malaria cohort (preprint)

ABSTRACT Importance Estimating the true burden of SARS-CoV-2 infection has been difficult in sub-Saharan Africa due to asymptomatic infections and inadequate testing capacity. Antibody responses from serologic surveys can provide an estimate of SARS-CoV-2 exposure at the population level. Objective To estimate SARS-CoV-2 seroprevalence, attack rates, and re-infection in eastern Uganda using serologic surveillance from 2020 to early 2022. Design Plasma samples from participants in the Program for Resistance, Immunology, Surveillance, and Modeling of Malaria in Uganda (PRISM) Border Cohort were obtained at four sampling intervals: October-November 2020; March-April 2021; August-September 2021; and February-March 2022. Setting: Tororo and Busia districts, Uganda. Participants 1,483 samples from 441 participants living in 76 households were tested. Each participant contributed up to 4 time points for SARS-CoV-2 serology, with almost half of all participants contributing at all 4 time points, and almost 90% contributing at 3 or 4 time points. Information on SARS-CoV-2 vaccination status was collected from participants, with the earliest reported vaccinations in the cohort occurring in May 2021. Main Outcome(s) and Measure(s) The main outcomes of this study were antibody responses to the SARS-CoV-2 spike protein as measured with a bead-based serologic assay. Individual-level outcomes were aggregated to population-level SARS-CoV-2 seroprevalence, attack rates, and boosting rates. Estimates were weighted by the local age distribution based on census data. Results By the end of the Delta wave and before widespread vaccination, nearly 70% of the study population had experienced SARS-CoV-2 infection. During the subsequent Omicron wave, 85% of unvaccinated, previously seronegative individuals were infected for the first time, and ∼50% or more of unvaccinated, already seropositive individuals were likely re-infected, leading to an overall 96% seropositivity in this population. Our results suggest a lower probability of re-infection in individuals with higher pre-existing antibody levels. We found evidence of household clustering of SARS-CoV-2 seroconversion. We found no significant associations between SARS-CoV-2 seroconversion and gender, household size, or recent Plasmodium falciparum malaria exposure. Conclusions and Relevance Findings: from this study are consistent with very high infection rates and re-infection rates for SARS-CoV-2 in a rural population from eastern Uganda throughout the pandemic.

Metagenomic next-generation sequencing to characterize etiologies of non-malarial fever in a cohort living in a high malaria burden area of Uganda (preprint)

Background: Causes of non-malarial fevers in sub-Saharan Africa remain understudied. We hypothesized that metagenomic next-generation sequencing (mNGS), which allows for broad genomic-level detection of infectious agents in a biological sample, can systematically identify potential causes of non-malarial fevers. Methods and Findings: The 212 participants in this study were of all ages and were enrolled in a longitudinal malaria cohort in eastern Uganda. Between December 2020 and August 2021, respiratory swabs and plasma samples were collected at 313 study visits where participants presented with fever and were negative for malaria by microscopy. Samples were analyzed using CZ ID, a web-based platform for microbial detection in mNGS data. Overall, viral pathogens were detected at 123 of 313 visits (39%). SARS-CoV-2 was detected at 11 visits, from which full viral genomes were recovered from nine. Other prevalent viruses included Influenza A (14 visits), RSV (12 visits), and three of the four strains of seasonal coronaviruses (6 visits). Notably, 11 influenza cases occurred between May and July 2021, coinciding with when the Delta variant of SARS-CoV-2 was circulating in this population. The primary limitation of this study is that we were unable to estimate the contribution of bacterial microbes to non-malarial fevers, due to the difficulty of distinguishing bacterial microbes that were pathogenic from those that were commensal or contaminants. Conclusions: These results revealed the co-circulation of multiple viral pathogens likely associated with fever in the cohort during this time period. This study illustrates the utility of mNGS in elucidating the multiple causes of non-malarial febrile illness. A better understanding of the pathogen landscape in different settings and age groups could aid in informing diagnostics, case management, and public health surveillance systems.

LLIN Evaluation in Uganda Project (LLINEUP2) – Factors associated with coverage and use of long‑lasting insecticidal nets following the 2020-21 national mass distribution campaign: a cross-sectional survey of 12 districts (preprint)

Background: In 2020-2021, long-lasting insecticidal nets (LLINs) were distributed nationwide in Uganda during the COVID-19 pandemic. A cross-sectional survey was conducted in 12 districts to evaluate the impact of the campaign 1-5 months after LLIN distribution. Methods: . During April-May 2021, households were randomly selected from target areas (1-7 villages) surrounding 12 government-run health facilities established as Malaria Reference Centres; at least 50 households were enrolled per cluster. Outcomes included household ownership of LLINs distributed through the universal coverage campaign (UCC) (at least one UCC LLIN), adequate coverage of UCC LLINs (at least one UCC LLIN per 2 residents), and use of LLINs (resident slept under a LLIN the previous night). Multivariate logistic regression models were used to identify household- and individual-level factors associated with outcomes, controlling for clustering around health facilities. Results: . In total, 634 households, with 3,342 residents and 1,631 bed-nets, were included. Most households (93.4%) owned at least 1 UCC LLIN, but only 56.8% were adequately covered by UCC LLINs. In an adjusted analysis, the factor most strongly associated with adequate coverage by UCC LLINs was fewer household residents (1-4 vs 7-14; adjusted odds ratio [aOR] 12.96, 95% CI 4.76-35.26, p<0.001; 5-6 vs 7-14 residents; aOR 2.99, 95% CI 1.21-7.42, p=0.018). Of the 3,166 residents of households that owned at least one UCC LLIN, only 1,684 (53.2%) lived in adequately covered households; 89.9% of these used an LLIN the previous night, compared to 1034 (69.8%) of 1,482 residents living in inadequately covered households. In an adjusted analysis, restricted to residents of inadequately covered households, LLIN use was higher in children under-five than those aged 5-15 years (aOR 3.04, 95% CI 2.08-4.46, p<0.001), and higher in household heads than distantly-related residents (aOR 3.94, 95% CI 2.38-6.51, p<0.001). Conclusions: . Uganda’s 2021-21 campaign was successful, despite the COVID-19 pandemic. In future campaigns, strategies should be adopted to ensure high LLIN coverage, particularly for larger households. A better understanding of the drivers of LLIN use within households is needed to guide future interventions, educational messages, and behaviour change communication strategies; school-aged children and distantly-related residents appear vulnerable and could be targeted.

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance. (preprint)

Investment in Africa over the past year with regards to SARS-CoV-2 genotyping has led to a massive increase in the number of sequences, exceeding 100,000 genomes generated to track the pandemic on the continent. Our results show an increase in the number of African countries able to sequence within their own borders, coupled with a decrease in sequencing turnaround time. Findings from this genomic surveillance underscores the heterogeneous nature of the pandemic but we observe repeated dissemination of SARS-CoV-2 variants within the continent. Sustained investment for genomic surveillance in Africa is needed as the virus continues to evolve, particularly in the low vaccination landscape. These investments are very crucial for preparedness and response for future pathogen outbreaks.

Impact of COVID-19 on routine malaria indicators in Uganda: An interrupted time series analysis (preprint)

Background: In March 2020, the government of Uganda implemented a strict lockdown policy in response to the COVID-19 pandemic. We performed an interrupted time series analysis (ITSA) to assess whether major changes in healthcare seeking behavior, malaria burden, and case management occurred after the onset of the COVID-19 epidemic. Methods Individual level data from all outpatient visits occurring from April 2017 through March 2021 at 17 facilities were analyzed. Outcomes included total outpatient visits, malaria cases, non-malarial visits, proportion of visits with suspected malaria, proportion of patients tested using rapid diagnostic tests (RDTs), and proportion of malaria cases prescribed artemether-lumefantrine (AL). Pre-COVID trends measured over a three-year period were extrapolated into the post-COVID period (April 2020- March 2021) using Poisson regression with generalized estimating equations or fractional regression. Effects of COVID-19 were estimated over the 12-month post-COVID period by dividing observed values by the predicted values and expressed as ratios. Results A total of 1,442,737 outpatient visits were recorded. Malaria was suspected in 55.3% of visits and 98.8% of these had a malaria diagnostic test performed. ITSA showed no differences in the observed versus predicted total outpatient visits, malaria cases, non-malarial visits, or proportion of visits with suspected malaria. However, in the second six months of the post-COVID period, there was a smaller mean proportion of patients tested with RDTs compared to predicted (Relative Prevalence Ratio (RPR) = 0.87, CI [0.78, 0.97]) and a smaller mean proportion of malaria cases prescribed AL (RPR = 0.94, CI [0.90, 0.99]. Conclusions There was evidence for a modest decrease in the proportion of RDTs used for malaria diagnosis and the proportion of patients prescribed AL in the second half of the post-COVID year, while other malaria indicators remained stable. Continued surveillance will be essential to monitor for changes in trends in malaria indicators so that Uganda can quickly and flexibly respond to challenges imposed by COVID-19.

A year of genomic surveillance reveals how the SARS-CoV-2 pandemic unfolded in Africa (preprint)

The progression of the SARS-CoV-2 pandemic in Africa has so far been heterogeneous and the full impact is not yet well understood. Here, we describe the genomic epidemiology using a dataset of 8746 genomes from 33 African countries and two overseas territories. We show that the epidemics in most countries were initiated by importations, predominantly from Europe, which diminished following the early introduction of international travel restrictions. As the pandemic progressed, ongoing transmission in many countries and increasing mobility led to the emergence and spread within the continent of many variants of concern and interest, such as B.1.351, B.1.525, A.23.1 and C.1.1. Although distorted by low sampling numbers and blind-spots, the findings highlight that Africa must not be left behind in the global pandemic response, otherwise it could become a breeding ground for new variants.

A SARS-CoV-2 lineage A variant (A.23.1) with altered spike has emerged and is dominating the current Uganda epidemic (preprint)

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) was first detected in March 2020 in Uganda. Recently the epidemic showed a shift of SARS-CoV-2 variant distribution and we report here newly emerging A sub-lineages, A.23 and A.23.1, encoding replacements in the spike protein, nsp6, ORF8 and ORF9, with A.23.1 the major virus lineage now observed in Kampala. Although the clinical impact of the A.23.1 variant is not yet clear it is essential to continue careful monitoring of this variant, as well as rapid assessment of the consequences of the spike protein changes for vaccine efficacy.

Operationalization of COVID-19 Rapid Diagnosis Using Xpert® Xpress SARS CoV-2 Assay in Resource-Limited Settings: Early Implementation Lessons From Uganda (preprint)

Introduction: The novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) that causes COVID-19 disease is a global challenge. Several countries have adopted testing, isolation, and tracing strategy towards the control of the COVID-19 pandemic, but access to rapid and accurate testing is still a global challenge. The  conventional PCR – based assay is the most commonly used test yet it has huge costs, infrastructural, and procurement logistical challenges. The Xpert® Xpress SARS-CoV-2 test is an automated in – vitro diagnostic test for the qualitative detection of nucleic acid from SARS-CoV-2 within a turnaround time of 60 minutes on the widely used GeneXpert Dx Instrument Systems. Here we document the best practices and challenges encountered with the operationalization of Xpert® Xpress SARS-CoV-2 testing in a resource-limited setting.Materials and Methods: The Xpert® Xpress SARS-CoV-2 implementation followed an operational work plan that included; Laboratory COVID-19 policy and planning, situational analysis of the Laboratory network, country Xpert® Xpress SARS-CoV-2 assay verification, and rollout at Mutukula Port Health Laboratory. The Laboratory strategy was based on a set of six objectives; conducting infrastructural modifications, building a strong COVID-19 testing capacity, developing robust Laboratory Quality and Information Management Systems, establishing a Bio-risk management and Bio-banking capacity.Results: The Xpert® Xpress SARS-CoV-2 testing implementation team that was appointed by the Ministry of Health (Uganda) successfully established the Xpert® Xpress SARS-CoV-2 testing Laboratory at Mutukula border in Uganda. As of 9th July 2020, this Laboratory had tested a total of 10,990 samples with a median turnaround time of 75 (IQR: 60 – 75) minutes for samples of persons entering through Mutukula Land Point of Entry as compared to the median TAT 1980 minutes before it was established. The laboratory had only one discordant result out of 20 panels in the inter-laboratory comparison retesting program.Conclusions: Implementation of Xpert® Xpress SARS-CoV-2 testing for rapid diagnosis of COVID-19 is feasible and significantly reduces the long TAT observed with conventional RT-PCR based testing. The operationalization of the Xpert® Xpress SARS-CoV-2 testing is largely dependent on the initial planning, adequacy of resources, and preparedness within the laboratory network. Challenges include; the difference in approaches to COVID-19 response, the attitude of truck-drivers/persons on Infection Prevention and Control measures, language barrier, and waste management issues.

Combination of Antibody based rapid diagnostic tests used in an algorithm may improve their performance in SARS CoV-2 diagnosis. (preprint)

Background: Globally response to the SARS-CoV-2 pandemic is highly limited by diagnostic methods. Currently, World Health Organization (WHO) recommends the use of molecular assays for confirmation of SARS-CoV-2 infection which are highly expensive and require specialized laboratory equipment. This is a limitation in mass testing and in low resource settings. SARS CoV-2 IgG/IgM antibody tests have had poor diagnostic performance that do not guarantee their use in diagnostics. In this study we demonstrate a concept of using a combination of RDTs in an algorithm to improve their performance for diagnostics. Method: Eighty six (86) EDTA whole blood samples were collected from SARS-CoV-2 positive cases admitted at Masaka and Mbarara Regional Referral Hospitals in Uganda. These were categorized from day when confirmed positive as follows; category A (0-3 days, 10 samples), category B (4-7 days, 20 samples), Category C (8-17 days, 11 samples) and Category D (18-28 days, 20 samples). Plasma was prepared, transported to the testing laboratory and stored at -200C prior to testing. A total of 13 RDTS were tested following manufacturers instructions. Data was entered in Microsoft Excel exported to STATA for computation of sensitivity and specificity. We computed for all possible combinations of 2 of the 13 RDTS (13C2) that were evaluated in parallel algorithm. Results: The individual sensitives of the RDTs ranged between 74% and 18% and there was a general increasing trend across the categories with days since PCR confirmation. A total of 78 possible combinations of the RDTs to be used in parallel was computated. The combinations of the 2 RDTS improved the sensitivities to 90%. Discussion: We demonstrate that use of RDTs in combinations can improve their overall sensitivity. This approach when used on a wider range of combination of RDTs may yield combinations that can give sensitivities that are of diagnostics relevance in mass testing and low resource setting.