District-Level Forecast of Achieving Trachoma Elimination as a Public Health Problem By 2030: An Ensemble Modelling Approach.

Assessing the feasibility of 2030 as a target date for global elimination of trachoma, and identification of districts that may require enhanced treatment to meet World Health Organization (WHO) elimination criteria by this date are key challenges in operational planning for trachoma programmes. Here we address these challenges by prospectively evaluating forecasting models of trachomatous inflammation-follicular (TF) prevalence, leveraging ensemble-based approaches. Seven candidate probabilistic models were developed to forecast district-wise TF prevalence in 11 760 districts, trained using district-level data on the population prevalence of TF in children aged 1-9 years from 2004 to 2022. Geographical location, history of mass drug administration treatment, and previously measured prevalence data were included in these models as key predictors. The best-performing models were included in an ensemble, using weights derived from their relative likelihood scores. To incorporate the inherent stochasticity of disease transmission and challenges of population-level surveillance, we forecasted probability distributions for the TF prevalence in each geographic district, rather than predicting a single value. Based on our probabilistic forecasts, 1.46% (95% confidence interval [CI]: 1.43-1.48%) of all districts in trachoma-endemic countries, equivalent to 172 districts, will exceed the 5% TF control threshold in 2030 with the current interventions. Global elimination of trachoma as a public health problem by 2030 may require enhanced intervention and/or surveillance of high-risk districts.

Accelerating Progress Towards the 2030 Neglected Tropical Diseases Targets: How Can Quantitative Modeling Support Programmatic Decisions?

Over the past decade, considerable progress has been made in the control, elimination, and eradication of neglected tropical diseases (NTDs). Despite these advances, most NTD programs have recently experienced important setbacks; for example, NTD interventions were some of the most frequently and severely impacted by service disruptions due to the coronavirus disease 2019 (COVID-19) pandemic. Mathematical modeling can help inform selection of interventions to meet the targets set out in the NTD road map 2021-2030, and such studies should prioritize questions that are relevant for decision-makers, especially those designing, implementing, and evaluating national and subnational programs. In September 2022, the World Health Organization hosted a stakeholder meeting to identify such priority modeling questions across a range of NTDs and to consider how modeling could inform local decision making. Here, we summarize the outputs of the meeting, highlight common themes in the questions being asked, and discuss how quantitative modeling can support programmatic decisions that may accelerate progress towards the 2030 targets.

Characterizing trachoma elimination using serology.

Trachoma is targeted for global elimination as a public health problem by 2030. Measurement of IgG antibodies in children is being considered for surveillance and programmatic decision-making. There are currently no guidelines for applications of serology, which represents a generalizable problem in seroepidemiology and disease elimination. We collated Chlamydia trachomatis Pgp3 and CT694 IgG measurements (63,911 children ages 1-9 years) from 48 serosurveys, including surveys across Africa, Latin America, and the Pacific Islands to estimate population-level seroconversion rates (SCR) along a gradient of trachoma endemicity. We propose a novel, generalizable approach to estimate the probability that population C. trachomatis transmission is below levels requiring ongoing programmatic action, or conversely is above levels that indicate ongoing interventions are needed. We provide possible thresholds for SCR at a specified level of certainty and illustrate how the approach could be used to inform trachoma program decision-making using serology.

De novo emergence of a remdesivir resistance mutation during treatment of persistent SARS-CoV-2 infection in an immunocompromised patient: a case report.

SARS-CoV-2 remdesivir resistance mutations have been generated in vitro but have not been reported in patients receiving treatment with the antiviral agent. We present a case of an immunocompromised patient with acquired B-cell deficiency who developed an indolent, protracted course of SARS-CoV-2 infection. Remdesivir therapy alleviated symptoms and produced a transient virologic response, but her course was complicated by recrudescence of high-grade viral shedding. Whole genome sequencing identified a mutation, E802D, in the nsp12 RNA-dependent RNA polymerase, which was not present in pre-treatment specimens. In vitro experiments demonstrated that the mutation conferred a ~6-fold increase in remdesivir IC50 but resulted in a fitness cost in the absence of remdesivir. Sustained clinical and virologic response was achieved after treatment with casirivimab-imdevimab. Although the fitness cost observed in vitro may limit the risk posed by E802D, this case illustrates the importance of monitoring for remdesivir resistance and the potential benefit of combinatorial therapies in immunocompromised patients with SARS-CoV-2 infection.

Plasmodium infection is associated with cross-reactive antibodies to carbohydrate epitopes on the SARS-CoV-2 Spike protein.

Sero-surveillance can monitor and project disease burden and risk. However, SARS-CoV-2 antibody test results can produce false positive results, limiting their efficacy as a sero-surveillance tool. False positive SARS-CoV-2 antibody results are associated with malaria exposure, and understanding this association is essential to interpret sero-surveillance results from malaria-endemic countries. Here, pre-pandemic samples from eight malaria endemic and non-endemic countries and four continents were tested by ELISA to measure SARS-CoV-2 Spike S1 subunit reactivity. Individuals with acute malaria infection generated substantial SARS-CoV-2 reactivity. Cross-reactivity was not associated with reactivity to other human coronaviruses or other SARS-CoV-2 proteins, as measured by peptide and protein arrays. ELISAs with deglycosylated and desialated Spike S1 subunits revealed that cross-reactive antibodies target sialic acid on N-linked glycans of the Spike protein. The functional activity of cross-reactive antibodies measured by neutralization assays showed that cross-reactive antibodies did not neutralize SARS-CoV-2 in vitro. Since routine use of glycosylated or sialated assays could result in false positive SARS-CoV-2 antibody results in malaria endemic regions, which could overestimate exposure and population-level immunity, we explored methods to increase specificity by reducing cross-reactivity. Overestimating population-level exposure to SARS-CoV-2 could lead to underestimates of risk of continued COVID-19 transmission in sub-Saharan Africa.

Lithium chloride functions as Newcastle disease virus-induced ER-stress modulator and confers anti-viral effect.

Newcastle disease is a severe clinical manifestation of avian species caused by Newcastle disease virus (NDV). Although several vaccination strategies are available to protect poultry against NDV infection, even then, outbreaks have been reported in the vaccinated birds. The lack of therapeutics against NDV makes the need for effective anti-viral drugs is of utmost importance. Lithium Chloride (LiCl) is a widely prescribed drug for the treatment of bipolar disorder, acute brain injuries, and chronic neurodegenerative diseases. Also, LiCl has been repurposed as an effective anti-viral drug for some viral infections. In the present work, we have investigated the efficacy of LiCl to inhibit NDV replication using in vitro, in ovo, and in vivo models. Our results collectively showed the modulation of NDV replication after the LiCl treatment. We also demonstrated that NDV induces endoplasmic reticulum stress (ER-stress), and a stress-inducible ER chaperone, glucose-regulating protein 78 (GRP78), was found to be over-expressed after NDV infection. Subsequently, the treatment of NDV infected cells with LiCl significantly reduced the transcript and protein levels of GRP78. Finally, we concluded that LiCl treatment protects the cells from ER-stress induced by the NDV infection.

De novo emergence of a remdesivir resistance mutation during treatment of persistent SARS-CoV-2 infection in an immunocompromised patient: A case report.

SARS-CoV-2 remdesivir resistance mutations have been generated in vitro but have not been reported in patients receiving treatment with the antiviral agent. We present a case of an immunocompromised patient with acquired B-cell deficiency who developed an indolent, protracted course of SARS-CoV-2 infection. Remdesivir therapy alleviated symptoms and produced a transient virologic response, but her course was complicated by recrudescence of high-grade viral shedding. Whole genome sequencing identified a mutation, E802D, in the nsp12 RNA-dependent RNA polymerase, which was not present in pre-treatment specimens. In vitro experiments demonstrated that the mutation conferred a ∼6-fold increase in remdesivir IC50 but resulted in a fitness cost in the absence of remdesivir. Sustained clinical and virologic response was achieved after treatment with casirivimab-imdevimab. Although the fitness cost observed in vitro may limit the risk posed by E802D, this case illustrates the importance of monitoring for remdesivir resistance and the potential benefit of combinatorial therapies in immunocompromised patients with SARS-CoV-2 infection.

Plasmodium infection induces cross-reactive antibodies to carbohydrate epitopes on the SARS-CoV-2 Spike protein.

Individuals with acute malaria infection generated high levels of antibodies that cross-react with the SARS-CoV-2 Spike protein. Cross-reactive antibodies specifically recognized the sialic acid moiety on N-linked glycans of the Spike protein and do not neutralize in vitro SARS-CoV-2. Sero-surveillance is critical for monitoring and projecting disease burden and risk during the pandemic; however, routine use of Spike protein-based assays may overestimate SARS-CoV-2 exposure and population-level immunity in malaria-endemic countries.

Analysis of codon usage pattern in the viral proteins of chicken anaemia virus and its possible biological relevance.

Chicken anaemia virus (CAV) is an important poultry pathogen. CAV infection can lead to severe immunosuppression and mortality in birds. The viral proteins (VP1, VP2 and VP3) are major protective immunogens that determine the pathotype of CAV strains. The factors influencing the synonymous codon usage bias and the nucleotide composition of the viral protein genes of CAV have not been studied. In the present study, we have analysed the synonymous codon usage pattern in VP1, VP2 and VP3 genes of CAV. Our results showed that all the genes have a low codon usage bias; however, this bias was slightly higher in the VP2 gene as compared to VP1 and VP3. The major contributing factor for this pattern of codon usage bias in CAV is mutational pressure followed by the host factors. The conclusion was drawn based on codon usage, correspondence analysis, ENC-GC3 plot and correlation analyses among different indices. The study will help us to understand the codon usage bias of CAV and related single-stranded DNA viruses which could further be used to explore their biology.