Disease epidemiology during the COVID-19 pandemic differed greatly across the globe. In contrast to early pandemic predictions, Africa recorded the fewest SARS-CoV-2 related hospitalizations and deaths. Hypotheses proposed to explain this paradox include underreporting, age demographics, climate, national mitigation strategies, lifestyle factors, pre-existing cross-reactive protection, and host genetic determinants. This traditional, narrative review evaluates these hypotheses investigated in the published literature, and highlights knowledge gaps which limit our understanding and obscure validation of potential explanations. It also discusses how responses to vaccines, the primary intervention sought to control infectious disease outbreaks, may vary both within the African population and across other continents. Potential explanations in the literature include pre-existing immunity, poor nutrition, immune modulating co-infections, comorbidities, microbiome composition, genetic polymorphisms, and demographic factors. Previous studies have shown that pre-existing (infection-derived) immunity or cross-reactive immune responses can augment vaccine-elicited positive responses and can protect against reinfection in a way similar to immunization. Conversely, there are also studies showing that prior immunity interferes with the efficacy of new vaccines through mechanisms like original antigenic sin and immune imprinting. Thus, there is need for more immunology studies to understand the relative contribution of pre-existing cross-reactive immune responses to the epidemiology of new pathogens. These studies are particularly essential to understand the differences between pandemic preparedness and population vulnerability, as well as to inform vaccine development and vaccine effectiveness monitoring studies. SARS-CoV-2 serves as an important case study to understand heterogeneity between and within populations in immune responses to both the pathogen and to vaccination. This understanding is crucial in informing vaccine research and development aimed at supporting the 100-day mission for when the next pandemic threat emerges.

INTRODUCTION:Public health today is challenged by a wide array of hazards that threaten humans, often resulting in high rates of morbidity and mortality when they strike. These events should be detected and responded to as early as possible to save lives and minimize their impact. The Epidemic Intelligence from Open Sources (EIOS) system leverages natural language processing and machine learning techniques for the early detection of public health events from open-source information using an all-hazards approach. In this study, we quantitatively evaluate the performance of the EIOS system for the early detection of outbreaks and health emergencies in the African region. METHODS:We retrospectively searched the EIOS system to determine if a signal was found on the system for each public health event notified to WHO by the 47 countries in the African region from 2018 to 2023. We computed the proportion of public health event detected by the EIOS system, its sensitivity, harmonic mean, and timeliness. We assessed the association between selected predictors (year of report, hazard type, subregion, source type, and language of source) and early detection of public health events on the EIOS system using a multivariable logistic regression model. RESULTS:We found a detection proportion of 81.0% and a sensitivity of 47.4%, with a harmonic mean of 59.8%. The proportion of events detected steadily increased over the years and sensitivity increased from a baseline of 44.1% in 2018 to 47.3% in 2023. Signals for more than 80.0% of the public health events notified to WHO in 28 countries were detected on the EIOS system. In 22 countries, signals of at least 50% of the public health events were detected early, that is, before official notification from the National Authorities to WHO. The median time between detection on the EIOS system and notification to WHO was zero days. We found that the type of hazard (infectious and zoonotic), the subregion (West and Central Africa), and the type of source (medical and social media) were associated with early detection. CONCLUSIONS:We conclude that the EIOS system performed well in detecting public health events in the African region early. However, some improvements are needed. We recommend increasing social media and local community radio sources on the EIOS system.

Enterotoxigenic Escherichia coli (ETEC) is a significant cause of diarrhoea in livestock and humans. The epidemiology of ETEC in animals remains understudied, prompting an investigation into the virulence factors and associated adhesins of ETEC in livestock from Western Kenya. Also, there is limited evidence supporting the role of livestock as possible zoonotic reservoirs for ETEC. ETEC strains harbour colonization factors/adhesins and enterotoxins, with animal ETECs exhibiting various adhesins (F4, F5, F6, F17, F18 and F41). Enterotoxins include heat- labile (LT) and heat- stable (ST) toxins and are further divided into LT- I and LT- II and STa and STb, respectively. Additional toxin combinations occur, with ETEC and Shiga toxin- producing E. coli (STEC) hybrids garnering public health significance. Here, we analysed faecal and mesenteric lymph node samples from diverse livestock across three Western Kenyan counties (Busia, Bungoma and Kakamega), using whole- genome sequencing. In silico screening determined the presence of AB5 and A2B5- like toxin genes, including cytolethal distending toxin (cdtABC) along with associated adhesins. To broaden the screening panel, adhesin genes identified were further characterized to identify both known and novel alleles, particularly focusing on human- ETEC colonization factors. Two estA alleles (estA-4-06, estA-6-02) and six eltAB- II toxin alleles (eltAB-II-a2-01, eltAB-II-a3-01, eltAB-II-c1-02, eltAB-II-c6-03, eltAB-II-c6-04 and eltAB-II-c7-02) were identified in livestock. Hybrid ETECs identified were ETEC/STEC present in 6.7% (4/60) of ETEC strains and ETEC with cdtABC type I. An A2B5- like tripartite toxin, potentially resembling the typhoid toxin, was detected in 8.7% (4/46) of the eltAB-II-positive strains. It may have unique effects on enterocytes distinct from known toxins. These findings expand our understanding of ETEC pathogenicity and genetic diversity in animal reservoirs, while also highlighting potential zoonotic risks. They broaden the toxin repertoire, offer adhesin- based vaccine candidates for livestock and provide valuable insights for future vaccine development and public health strategies in the Lake Victoria Crescent ecosystem and beyond.

Antimicrobial resistance (AMR) is a significant and growing threat to human health. A recent United Nations General Assembly declaration highlights that those in need must have sustained access to effective treatments. In the absence of a reliable supply of new drugs, pressure on existing drugs can be reduced by minimising demand. Routes to reducing demand include: promotion of WASH (access to clean water, sanitation and hygiene) and Universal Health Coverage (UHC); improved infection control in health care settings; and continued efforts to curtail drug use in agriculture. This is a One Health strategy, requiring coordinated action across the human, livestock and environmental sectors.

Transmissibility, the ability to spread within host populations, is a prerequisite for a pathogen to have epidemic or pandemic potential. Here, we estimate the phylogenies of human infectivity and transmissibility using 1,408 genome sequences from 743 distinct RNA virus species/types in 59 genera. By repeating this analysis using data sets censored by virus discovery date, we explore how temporal changes in the known diversity of RNA viruses-especially recent increases in recognized nonhuman viruses-have altered these phylogenies. Over time, we find significant increases in the proportion of RNA virus genera estimated to have a nonhuman-infective ancestral state, in the fraction of distinct human virus lineages that are purely human-transmissible or strictly zoonotic (compared to mixed lineages), and in the number of human viruses with nearest relatives known not to infect humans. Our results are consistent with viruses that are capable of spreading in human populations commonly emerging from a nonhuman reservoir. This is more likely in lineages that already contain human-transmissible viruses but is rare in lineages that contain only strictly zoonotic viruses.

Abstract Background Understanding how the COVID-19 pandemic evolved under control measures is crucial to tackle the SARS-CoV-2 virus spread. Laos, a country bordering China but with late occurrence and low burden of COVID-19 compared to its neighbouring countries, was used for a case study. Methods A transmission model with disease reporting was proposed to investigate the impact of control measures on the SARS-CoV-2 virus spread in Laos from April 2021 to May 2022. It was assumed that the transmission rate changed with people’s behaviours, control measures and emerging variants; susceptibility decreased with vaccination and infection. Bayesian inference was used for model calibration to data of confirmed cases, deaths, and recoveries, and the deviance information criterion was used to select the best model variant. Results Our model including Non-pharmaceutical interventions (NPIs), behaviour change, vaccination, and changing variants well explained the three waves in Laos. The Alpha variant was estimated to have a basic reproduction number of 1.55 (95% CrI: 1.47–1.64) and was replaced by the Delta variant from September 2021 which was 1.88 (95% CrI: 1.77–2.01) times more transmissible; the Delta variant was replaced by Omicron variant from March 2022 which was 3.33 (95% CrI: 2.84–3.74) times more transmissible. The Delta variant was the most severe with a case fatality rate of 1.05% (95% CrI: 0.96–1.15%) while the Alpha variant and Omicron variant were much milder. The ascertainment rate was low and variable: first decreasing from 13.2 to 1.8% by 23 May 2021, and then increasing to 23.4% by 15 March 2022. Counterfactual simulations indicated that vaccination played strong roles in reducing infections even under the emergence of immune escape variants while behaviour change delayed but might not flatten the peak of outbreaks. Conclusions The three waves of Laos’ epidemics were due to the invasion of more transmissible and immune escape variants that affected the herd immunity built via vaccination and infection. Even with immunity waning and the escape of new variants, vaccination was still the major contributor to control COVID-19 and combining behaviour changes and vaccination would best suppress future outbreaks of COVID-19.

BackgroundThe human gut microbiome harbours diverse species of archaea, bacteria, fungi, protists and viruses. To date, most gut microbiome studies have focused on bacteria, neglecting other microbial communities. Consequently, less is known about the diversity and abundance of the latter. Here, we aimed to characterise the diversity and composition of protists in the gut of preschool-aged children (PSAC) in rural Zimbabwe relative to host age, sex, and schistosome infection status.MethodsThe gut protist of 113 PSAC (1–5 years) was examined via shotgun metagenomic sequencing and analysed for diversity. Variation in protist abundance with host and environmental factors was analysed by permutational multivariate analysis of variance (PERMANOVA). To investigate how the composition of specific taxa varies across age, sex, nutritional measures and Schistosoma hematobium infection status, analysis of the composition of microbiomes (ANCOM) was used.ResultsEighty protist genera were identified, and the most abundant genera detected was Blastocystis. The prevalence of pathogenic protists was comparatively low, with 12.4% and 3.4% of the participants’ gut colonised by E. histolytica and Cryptosporidium, respectively. Of all the independent variables only S. haematobium infection showed significant relationship with the structure of the gut protist, being associated with increases in Peronospora, Pseudoperonospora, Plasmopara and Blastocystis (FDR= 0.009).SummaryThis study provides data on the prevalence and diversity of the gut protists in young Zimbabwean children with an emphasis on the host factors; age, sex and schistosome infection status. Our results showed no association between the host factors investigated, including anthropometric measures adjusted for age and the intestinal protist composition and structure, but S. haematobium infection status was associated with composition of specific taxa. There is a need for more studies determining how pathogenic protist interact with non-pathogenic protist in people exhibiting clinical symptoms to inform therapy and nutraceuticals.

Schistosomiasis is the second most important parasitic disease of public health importance in Africa, affecting over 50 million children aged <5 years old. Schistosomiasis control has focused on treating school-aged children (>6 years) and adults through mass drug administration (MDA). Following the recent development of a paediatric praziquantel (PZQ) formulation for children aged <5 years, there are now concerted efforts to determine optimal and effective ways to integrate treatment of these children into national schistosomiasis control programmes. In this opinion article we outline the pathway for successful drug access, delivery, and mainstreaming of the new formulation in endemic country health systems. Effective and sustained paediatric schistosomiasis treatment is an important target of the 2030 World Health Organization (WHO) neglected tropical diseases (NTDs) roadmap.

BACKGROUND:West Nile virus (WNV) outbreaks in birds, humans, and livestock have occurred in multiple areas in Europe and have had a significant impact on animal and human health. The patterns of emergence and spread of WNV in Europe are very different from those in the US and understanding these are important for guiding preparedness activities. METHODS:We mapped the evolution and spread history of WNV in Europe by incorporating viral genome sequences and epidemiological data into phylodynamic models. Spatially explicit phylogeographic models were developed to explore the possible contribution of different drivers to viral dispersal direction and velocity. A "skygrid-GLM" approach was used to identify how changes in environments would predict viral genetic diversity variations over time. FINDINGS:Among the six lineages found in Europe, WNV-2a (a sub-lineage of WNV-2) has been predominant (accounting for 73% of all sequences obtained in Europe that have been shared in the public domain) and has spread to at least 14 countries. In the past two decades, WNV-2a has evolved into two major co-circulating clusters, both originating from Central Europe, but with distinct dynamic history and transmission patterns. WNV-2a spreads at a high dispersal velocity (88km/yr-215 km/yr) which is correlated to bird movements. Notably, amongst multiple drivers that could affect the spread of WNV, factors related to land use were found to strongly influence the spread of WNV. Specifically, the intensity of agricultural activities (defined by factors related to crops and livestock production, such as coverage of cropland, pasture, cultivated and managed vegetation, livestock density) were positively associated with both spread direction and velocity. In addition, WNV spread direction was associated with high coverage of wetlands and migratory bird flyways. CONCLUSION:Our results suggest that-in addition to ecological conditions favouring bird- and mosquito- presence-agricultural land use may be a significant driver of WNV emergence and spread. Our study also identified significant gaps in data and the need to strengthen virological surveillance in countries of Central Europe from where WNV outbreaks are likely seeded. Enhanced monitoring for early detection of further dispersal could be targeted to areas with high agricultural activities and habitats of migratory birds.

Urbanization is predicted to be a key driver of disease emergence through human exposure to novel, animal -borne pathogens. However, while we suspect that urban landscapes are primed to expose people to novel animal -borne diseases, evidence for the mechanisms by which this occurs is lacking. To address this, we studied how bacterial genes are shared between wild animals, livestock, and humans (n = 1,428) across Nairobi, Kenya-one of the world's most rapidly developing cities. Applying a multilayer network framework, we show that low biodiversity (of both natural habitat and vertebrate wildlife communities), coupled with livestock management practices and more densely populated urban environments, promotes sharing of Escherichia coli-borne bacterial mobile genetic elements between animals and humans. These results provide empirical support for hypotheses linking resource provision, the biological simplification of urban landscapes, and human and livestock demography to urban dynamics of cross-species pathogen transmission at a landscape scale. Urban areas where high densities of people and livestock live in close association with synanthropes (species such as rodents that are more competent reservoirs for zoonotic pathogens) should be prioritized for disease surveillance and control.

There is a current global push to identify and implement best practice for delivering maximum impact from development research in low-income and middle-income countries. Here, we describe a model of research and capacity building that challenges traditional approaches taken by western funders in Africa. Tackling Infections to Benefit Africa (TIBA) is a global health research and delivery partnership with a focus on strengthening health systems to combat neglected tropical diseases, malaria and emerging pathogens in Africa. Partners are academic and research institutions based in Ghana, Sudan, Rwanda, Uganda, Kenya, Tanzania, Zimbabwe, Botswana, South Africa and the UK. Fifteen other African countries have participated in TIBA activities. With a starting budget of under £7 million, and in just 4 years, TIBA has had a verified impact on knowledge, policy practice and capacity building, and on national and international COVID-19 responses in multiple African countries. TIBA’s impact is shown in context-specific metrics including: strengthening the evidence base underpinning international policy on neglected tropical diseases; 77% of research publications having Africa-based first and/or last authors; postgraduate, postdoctoral and professional training; career progression for African researchers and health professionals with no net brain drain from participating countries; and supporting African institutions. Training in real-time SARS-CoV-2 viral genome sequencing provided new national capabilities and capacities that contributed to both national responses and global health security through variant detection and tracking. TIBA’s experience confirms that health research for Africa thrives when the agenda and priorities are set in Africa, by Africans, and the work is done in Africa. Here, we share 10 actionable recommendations for researchers and funders from our lessons learnt.

For the last two decades, the human infection frequency of Escherichia coli O157 (O157) in Scotland has been 2.5-fold higher than in England and Wales. Results from national cattle surveys conducted in Scotland and England and Wales in 2014/2015 were combined with data on reported human clinical cases from the same time frame to determine if strain differences in national populations of O157 in cattle could be associated with higher human infection rates in Scotland. Shiga toxin subtype (Stx) and phage type (PT) were examined within and between host (cattle vs human) and nation (Scotland vs England and Wales). For a subset of the strains, whole genome sequencing (WGS) provided further insights into geographical and host association. All three major O157 lineages (I, II, I/II) and most sub-lineages (Ia, Ib, Ic, IIa, IIb, IIc) were represented in cattle and humans in both nations. While the relative contribution of different reservoir hosts to human infection is unknown, WGS analysis indicated that the majority of O157 diversity in human cases was captured by isolates from cattle. Despite comparable cattle O157 prevalence between nations, strain types were localized. PT21/28 (sub-lineage Ic, Stx2a+) was significantly more prevalent in Scottish cattle [odds ratio (OR) 8.7 (2.3–33.7; P <0.001] and humans [OR 2.2 (1.5–3.2); P <0.001]. In England and Wales, cattle had a significantly higher association with sub-lineage IIa strains [PT54, Stx2c; OR 5.6 (1.27–33.3); P =0.011] while humans were significantly more closely associated with sub-lineage IIb [PT8, Stx1 and Stx2c; OR 29 (4.9–1161); P <0.001]. Therefore, cattle farms in Scotland were more likely to harbour Stx2a+O157 strains compared to farms in E and W ( P <0.001). There was evidence of limited cattle strain migration between nations and clinical isolates from one nation were more similar to cattle isolates from the same nation, with sub-lineage Ic (mainly PT21/28) exhibiting clear national association and evidence of local transmission in Scotland. While we propose the higher rate of O157 clinical cases in Scotland, compared to England and Wales, is a consequence of the nationally higher level of Stx2a+O157 strains in Scottish cattle, we discuss the multiple additional factors that may also contribute to the different infection rates between these nations.

Antimicrobial resistance (AMR) is a major threat to global health. Understanding the emergence, evolution, and transmission of individual antibiotic resistance genes (ARGs) is essential to develop sustainable strategies combatting this threat. Here, we use metagenomic sequencing to analyse ARGs in 757 sewage samples from 243 cities in 101 countries, collected from 2016 to 2019. We find regional patterns in resistomes, and these differ between subsets corresponding to drug classes and are partly driven by taxonomic variation. The genetic environments of 49 common ARGs are highly diverse, with most common ARGs carried by multiple distinct genomic contexts globally and sometimes on plasmids. Analysis of flanking sequence revealed ARG-specific patterns of dispersal limitation and global transmission. Our data furthermore suggest certain geographies are more prone to transmission events and should receive additional attention.

The wastewater microbiome contains a multitude of resistant bacteria of human origin, presenting an opportunity for surveillance of resistance in the general population. However, wastewater microbial communities are also influenced by clinical sources, such as hospitals. Identifying signatures of the community and hospital resistome in wastewater is needed for interpretation and risk analysis. In this study, we compare the resistome and microbiome of hospital, community, and mixed municipal wastewater to investigate how and why the composition of these different sites differ. We conducted shotgun metagenomic analysis on wastewater samples from eight wastewater treatment plants (WWTPs), four hospitals, and four community sites in Scotland, using a paired sampling design. Cluster analysis and source attribution random forest models demonstrated that the hospital resistome was distinct from community and WWTP resistomes. Hospital wastewater had a higher abundance and diversity of resistance genes, in keeping with evidence that hospitals act as a reservoir and enricher of resistance. However, this distinctive 'hospital' signature appeared to be weak in the resistome of downstream WWTPs, likely due to dilution. We conclude that hospital and community wastewater resistomes differ, with the hospital wastewater representing a reservoir of patient- and hospital environment-associated bacteria. However, this 'hospital' signature is transient and does not overwhelm the community signature in the resistome of the downstream WWTP influent.

Background SARS-CoV-2 infections and deaths have been lower in Africa than in other continents, which could be attributed to previous exposure to other pathogens that induce protective cross-immunity or modify the immune phenotype. We aimed to identify and characterise pre-existing cross-reactive immune responses to SARS-CoV-2 in an African population.Methods In this cross-sectional study, we determined the prevalence of SARS-CoV-2 serological cross-reactivity of 339 previously collected pre-pandemic (2000-19) serum samples from adults living in four villages in Zimbabwe (Mupfure, Mutoko, Chiredzi, and Murewa). We tested samples with a COVID-19 rapid diagnostic test then screened for cross-reactivity with peptides from the proteomes of seven human coronaviruses. We compared peptide location, coverage, and intensity and matched peptides predicted to be B-cell epitopes to the Human Immune Epitope Database (HIED).Findings Pre-SARS-CoV-2 serum samples from Mupfure and Murewa showed an overall prevalence of cross-reactivity with the SARS-CoV-2 rapid diagnostic test of 31.9% (95% CI 26.93-37.11). Peptide analysis of samples from all four villages highlighted complex IgM and IgG response profiles against peptides in the spike, nucleocapsid, and polyprotein 1AB proteins across all coronaviruses. Interrogating SARS-CoV-2 peptides recognised by IgG and IgM from the Zimbabwean serum samples against the HIED showed that most were either unique to SARS-CoV-2 or shared only with other betacoronaviruses. However, some SARS-CoV-2 peptides shared motifs with antigens from pathogens endemic to Zimbabwe, including Trypanosoma spp and Plasmodium spp, plant and food immunogens, and human autoantigens.Interpretation The effect of these cross-reactive antibodies on SARS-CoV-2 infection or COVID-19 is unknown; however, these antibodies should be considered when interpreting SARS-CoV-2 seroepidemiology studies and evaluating outcomes of COVID-19 vaccine trials in Africa. This study also calls for further characterisation of SARs-CoV-2 immune phenotypes and responses in African populations.Funding Scottish Funding Council Global Challenges Research Fund Grant at the University of Edinburgh; UK National Institute for Health Research.Copyright (c) 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license.

Background Sars-CoV-2, the causative agent of COVID-19, has led to more than 226,000 deaths in the UK and multiple risk factors for mortality including age, sex and deprivation have been identified. This study aimed to identify which individual indicators of the Scottish Index of Multiple Deprivation (SIMD), an area-based deprivation index, were predictive of mortality. Methods This was a prospective cohort study of anonymised electronic health records of 710 consecutive patients hospitalised with Covid-19 disease between March and June 2020 in the Lothian Region of Southeast Scotland. Data sources included automatically extracted data from national electronic platforms and manually extracted data from individual admission records. Exposure variables of interest were SIMD quintiles and 12 indicators of deprivation deemed clinically relevant selected from the SIMD. Our primary outcome was mortality. Age and sex adjusted univariable and multivariable analyses were used to determine measures of association between exposures of interest and the primary outcome. Results After adjusting for age and sex, we found an increased risk of mortality in the more deprived SIMD quintiles 1 and 3 (OR 1.75, CI 0.99–3.08, p = 0.053 and OR 2.17, CI 1.22–3.86, p = 0.009, respectively), but this association was not upheld in our multivariable model containing age, sex, Performance Status and clinical parameters of severity at admission. Of the 12 pre-selected indicators of deprivation, two were associated with greater mortality in our multivariable analysis: income deprivation rate categorised by quartile (Q4 (most deprived): 2.11 (1.20–3.77) p = 0.011)) and greater than expected hospitalisations due to alcohol per SIMD data zone (1.96 (1.28–3.00) p = 0.002)). Conclusions SIMD as an aggregate measure of deprivation was not predictive of mortality in our cohort when other exposure measures were accounted for. However, we identified a two-fold increased risk of mortality in patients residing in areas with greater income-deprivation and/or number of hospitalisations due to alcohol. In areas where aggregate measures fail to capture pockets of deprivation, exploring the impact of specific SIMD indicators may be helpful in targeting resources to residents at risk of poorer outcomes from Covid-19.

Antibiotic usage in livestock has been suggested as a driver of antimicrobial resistance in human and livestock populations. This has contributed to the implementation of stewardship programs to curtail usage of antibiotics in livestock. However, the consequences of antibiotic curtailment in livestock on human health are poorly understood. There is the potential for increases in the carriage of pathogens such as Salmonella spp. in livestock, and subsequent increases in human foodborne disease. We use a mathematical model fitted to four case studies, ampicillin and tetracycline usage in fattening pig and broiler poultry populations, to explore the impact of curtailing antibiotic usage in livestock on salmonellosis in humans.Increases in the daily incidence of salmonellosis and a decrease in the proportion of resistant salmonellosis were identified following curtailment of antibiotic usage in livestock. The extent of these increases in human foodborne disease ranged from negligible, to controllable through interventions to target the farm-to-fork pathway. This study provides a motivating example of one plausible scenario following curtailment of antibiotic usage in livestock and suggests that a focus on ensuring good farm-to-fork hygiene and livestock biosecurity is sufficient to mitigate the negative human health consequences of antibiotic stewardship in livestock populations.