Mhairi J. McCormack

Serological data provide important insights into SARS-CoV-2 transmission and immunity, particularly in regions with limited routine surveillance such as sub-Saharan Africa. However, antibody waning and boosting following reinfection or vaccination remain poorly characterised, complicating interpretation of serological measurements. Improved understanding of these dynamics is critical for accurate epidemiological inference. Modelling longitudinal serological data provides a means to quantify antibody kinetics and reconstruct infection histories. We analysed 15,679 neutralising antibody (nAb) titres from 1,675 unvaccinated, HIV-uninfected participants in urban (Lilongwe) and rural (Karonga) Malawi (February 2021–April 2022). NAb titres against ancestral B.1, Beta, Delta, and Omicron (BA.1/BA.2) viruses were measured using an HIV-based SARS-CoV-2 pseudotyped virus neutralisation assay. A multi-level Bayesian model was used to reconstruct infection histories and antibody kinetics. The model identified 429 infections (95% credible interval 417–441), including 39 (9.1%) that had not been identified by traditional seroconversion-based thresholds. Antibody levels waned rapidly, with 48% (0.403–0.560) of the acute boost remaining after three months and only 5% (0.027–0.098) after one year. Pre-Omicron infections generated stronger antibody boosts than Omicron infections. Responses varied, with individuals clustering into low and high responders. Cross-reactive responses extended across substantial antigenic distances - Omicron infections induced broader immunity. Seroincidence was higher in Lilongwe than in Karonga (0.41 vs. 0.27 infections per person per three months), driven by the early 2022 Omicron wave. Reinfections were common, particularly among adults and urban residents. SARS-CoV-2 nAb responses following infection were heterogeneous and declined rapidly. This rapid waning underscores the importance of vaccination for sustained protection, while cross-reactivity suggests only partial immunity from prior variants. Identifying reinfections is essential for understanding transmission and finding populations at higher repeat infection risk, particularly where routine surveillance is limited.

Serological data provide important insights into SARS-CoV-2 transmission and immunity, particularly in regions with limited routine surveillance such as sub-Saharan Africa. However, antibody waning and boosting following reinfection or vaccination remain poorly characterised, complicating interpretation of serological measurements. Improved understanding of these dynamics is critical for accurate epidemiological inference. Modelling longitudinal serological data provides a means to quantify antibody kinetics and reconstruct infection histories. We analysed 15,679 neutralising antibody (nAb) titres from 1,675 unvaccinated, HIV-uninfected participants in urban (Lilongwe) and rural (Karonga) Malawi (February 2021 - April 2022). NAb titres against ancestral B.1, Beta, Delta, and Omicron (BA.1/BA.2) viruses were measured using an HIV-based SARS-CoV-2 pseudotyped virus neutralisation assay. A multi-level Bayesian model was used to reconstruct infection histories and antibody kinetics. The model identified 429 infections (95% credible interval 417-441), including 39 (9·1%) that had not been identified by traditional seroconversion-based thresholds. Antibody levels waned rapidly, with 48% (0·403-0·560) of the acute boost remaining after three months and only 5% (0·027-0·098) after one year. Pre-Omicron infections generated stronger antibody boosts than Omicron infections. Responses varied, with individuals clustering into low and high responders. Cross-reactive responses extended across substantial antigenic distances - Omicron infections induced broader immunity. Seroincidence was higher in Lilongwe than in Karonga (0·41 vs. 0·27 infections per person per three months), driven by the early 2022 Omicron wave. Reinfections were common, particularly among adults and urban residents. SARS-CoV-2 nAb responses following infection were heterogeneous and declined rapidly. This rapid waning underscores the importance of vaccination for sustained protection, while cross-reactivity suggests only partial immunity from prior variants. Identifying reinfections is essential for understanding transmission and finding populations at higher repeat infection risk, particularly where routine surveillance is limited.

Background: Serological data provide important insights into SARS-CoV-2 transmission and immunity, particularly in regions with limited routine surveillance such as sub-Saharan Africa. However, antibody waning and boosting following reinfection or vaccination remain poorly characterised, complicating interpretation of serological measurements. Improved understanding of these dynamics is critical for accurate epidemiological inference. Modelling longitudinal serological data provides a means to quantify antibody kinetics and reconstruct infection histories. Methods: We analysed 15,679 neutralising antibody (nAb) titres from 1,675 unvaccinated, HIV-uninfected participants in urban (Lilongwe) and rural (Karonga) Malawi (February 2021 - April 2022). NAb titres against ancestral B.1, Beta, Delta, and Omicron (BA.1/BA.2) viruses were measured using an HIV-based SARS-CoV-2 pseudotyped virus neutralisation assay. A multi-level Bayesian model was used to reconstruct infection histories and antibody kinetics. Findings: The model identified 429 infections (95% credible interval 417-441), including 39 (9·1%) that had not been identified by traditional seroconversion-based thresholds. Antibody levels waned rapidly, with 48% (0·403-0·560) of the acute boost remaining after three months and only 5% (0·027-0·098) after one year. Pre-Omicron infections generated stronger antibody boosts than Omicron infections. Responses varied, with individuals clustering into low and high responders. Cross-reactive responses extended across substantial antigenic distances - Omicron infections induced broader immunity. Seroincidence was higher in Lilongwe than in Karonga (0·41 vs. 0·27 infections per person per three months), driven by the early 2022 Omicron wave. Reinfections were common, particularly among adults and urban residents. Interpretation: SARS-CoV-2 nAb responses following infection were heterogeneous and declined rapidly. This rapid waning underscores the importance of vaccination for sustained protection, while cross-reactivity suggests only partial immunity from prior variants. Identifying reinfections is essential for understanding transmission and finding populations at higher repeat infection risk, particularly where routine surveillance is limited.

SARS-CoV-2 transmission in Malawi remains unclear due to high proportions of mild/asymptomatic infections and limited diagnostics. Existing seroprevalence studies in Malawi have primarily used convenience samples and enzyme-linked immunosorbent assays (ELISAs). We assessed SARS-CoV-2 neutralisation in a longitudinal Malawian population-based cohort, assessing protective immunity post-infection and vaccination. Sera were obtained from rural (Karonga, n = 958) and urban (Lilongwe, n = 918) based participants at three-monthly intervals (February 2021-April 2022). Neutralising antibodies against SARS-CoV-2 were measured using human immunodeficiency (HIV)-based pseudotype assays in HIV-uninfected participants, and vesicular stomatitis virus-based assays in HIV-infected participants and an HIV-uninfected subset. Nucleocapsid ELISAs identified vaccinated participants also infected. SARS-CoV-2 neutralisation profiles increased in complexity over time from rising vaccination coverage and emerging variants. Neutralising antibody prevalence was higher in Lilongwe than Karonga (68.1% (CI 63.5–72.4) vs. 45.4% (CI 41.6–49.3), Survey 4). Hybrid immune and solely vaccinated participants exhibited higher titres than those solely infected. Children < 15 years had the lowest neutralising antibody titres among infected (not vaccinated) participants. People living with HIV had lower neutralising responses than those HIV-uninfected, particularly post vaccination. We therefore recommend surveillance of children and people living with HIV as low neutralisation responses increase reinfection risk. COVID-19 vaccination should be prioritised for HIV-infected individuals.

Retroviral pseudotype-based virus neutralisation assays are widely used to estimate functional immunity, but may be unsuitable for testing human immunodeficiency virus (HIV)-infected individuals receiving integrase inhibitor treatment. We evaluated these assays for measuring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and hepatitis C virus (HCV) neutralisation in people living with HIV. SARS-CoV-2 neutralisation was assessed using HIV-based SARS-CoV-2 pseudoviruses in sera from a longitudinal Malawian cohort (n = 1,876), detecting neutralisation across timepoints in 10.5–54.5% of HIV-uninfected vs. 85.5–93.9% of HIV-infected participants (n = 96). HIV-infected sera were re-tested using vesicular stomatitis virus (VSV)-based SARS-CoV-2 pseudoviruses, estimating seroprevalence at 5.6–65.2%, suggesting HIV-based assays overestimate neutralisation. HIV-based VSV-glycoprotein(G) pseudoviruses confirmed non-specific inhibition in 75.0-87.9% of HIV-infected participants. HCV neutralisation was assessed in UK-based HCV patients (n = 100, n = 90 HIV-infected) using murine leukaemia virus (MLV)-based HCV pseudoviruses. Non-HCV-specific inhibition was detected in integrase inhibitor recipients. Median neutralisation of MLV(HCV) pseudoviruses was higher in integrase inhibitor recipients (71.8% vs. 21.3%). Testing HIV(SARS-CoV-2) and MLV(HCV) pseudoviruses against antiretroviral drugs showed interference by integrase inhibitors (specifically, dolutegravir). Isolating IgG from serum removed the interference by residual drugs. Retrovirus-based assays are therefore unsuitable for testing individuals receiving integrase inhibitors. Protective immunity to viruses has likely been over-reported in HIV prevalent populations.

Appropriate interpretation of environmental signals facilitates niche specificity in pathogenic bacteria. However, the responses of niche-specific pathogens to common host signals are poorly understood. d-Serine (d-ser) is a toxic metabolite present in highly variable concentrations at different colonization sites within the human host that we previously found is capable of inducing changes in gene expression. In this study, we made the striking observation that the global transcriptional response of three Escherichia coli pathotypes – enterohaemorrhagic E. coli (EHEC), uropathogenic E. coli (UPEC) and neonatal meningitis-associated E. coli (NMEC) – to d-ser was highly distinct. In fact, we identified no single differentially expressed gene common to all three strains. We observed the induction of ribosome-associated genes in extraintestinal pathogens UPEC and NMEC only, and the induction of purine metabolism genes in gut-restricted EHEC, and UPEC indicating distinct transcriptional responses to a common signal. UPEC and NMEC encode dsdCXA – a genetic locus required for detoxification and hence normal growth in the presence of d-ser. Specific transcriptional responses were induced in strains accumulating d-ser (WT EHEC and UPEC/NMEC mutants lacking the d-ser-responsive transcriptional activator DsdC), corroborating the notion that d-ser is an unfavourable metabolite if not metabolized. Importantly, many of the UPEC-associated transcriptome alterations correlate with published data on the urinary transcriptome, supporting the hypothesis that d-ser sensing forms a key part of urinary niche adaptation in this pathotype. Collectively, our results demonstrate distinct pleiotropic responses to a common metabolite in diverse E. coli pathotypes, with important implications for niche selectivity.