Abrar Ahmad Chughtai

Background and Aims: Severe acute respiratory infections (SARI) remain a major cause of global morbidity and mortality, with a disproportionate burden in low‐ and middle‐income countries (LMICs). Although in‐hospital mortality is frequently reported, deaths occurring after hospital discharge remain poorly documented. We aimed to synthesise the available evidence on the causes and contributing factors of in‐hospital and post‐discharge mortality among patients hospitalised with SARI in LMICs. Methods: We conducted a scoping review following the Arksey and O'Malley framework and PRISMA‐ScR guidelines. PubMed, Web of Science, Scopus, and CINAHL were searched for studies published between January 2000 and October 2025 that reported in‐hospital and/or post‐discharge mortality among patients with SARI in LMICs. Findings were synthesised narratively to describe factors associated with in‐hospital and post‐discharge mortality, as well as reported causes of death. Results: Twenty‐nine studies from 13 LMICs met the inclusion criteria. All reported in‐hospital mortality (range: 0.4%–39.3%), while four reported post‐discharge mortality (range: 0.6%–5.7%). Thirteen studies examined factors associated with mortality. In‐hospital mortality was associated with older age, male sex, comorbidities, markers of severe clinical presentation, specific respiratory pathogens, and delayed healthcare seeking. Only one study specifically evaluated factors associated with post‐discharge mortality, identifying respiratory difficulty, underlying heart disease, and longer hospital stay among children, and chronic obstructive pulmonary disease and intensive care unit admission among adults as risk factors. Pathogen‐specific causes of in‐hospital death were reported in a single study, and no study reported definitive causes of post‐discharge mortality. Conclusion: Evidence on SARI‐associated mortality in LMICs is largely confined to in‐hospital outcomes, with limited assessment of post‐discharge mortality or causes of death. Standardised post‐discharge follow‐up and systematic cause‐of‐death reporting are needed to inform clinical care, strengthen surveillance, and support targeted interventions to reduce preventable SARI‐associated mortality in LMICs.

This study aimed to integrate Nigerian Pidgin English (NPE) into the Artificial Intelligence system EPIWATCH ^® , with the aim of providing early detection and enhanced surveillance of infectious disease outbreaks in Nigeria. The widespread use of NPE as a lingua franca, spoken by over 75 million people in Africa, improves interaction and communication within communities across Nigeria. Key search terms were translated into NPE and incorporated into EPIWATCH ^® for surveillance. Using publicly available outbreak reports collected by EPIWATCH ^® from Nigeria between 2018 and 2023, we conducted a descriptive analysis to compare outbreak detection patterns before and after the integration of NPE into the system. We observed a 315% increase in EPIWATCH ^® outbreak reports in March 2024 compared to the March median across 2018 to 2023, following NPE language integration. This study demonstrates the potential of leveraging technology and linguistic diversity to improve disease surveillance using open source intelligence (OSINT) and response efforts in Nigeria. Findings should be interpreted in light of the short prospective time frame, scope, contextual factors, and public source constraints, which may limit generalisability and nuance in assessing the impact of NPE integration.

On 6 October 2022, the first cholera outbreak in three decades was reported in Lebanon by the Ministry of Public Health (MoPH). The outbreak spread across all 8 governorates (23 out of 26 districts). From October 2022 to June 2023, a total of 8,072 cases (including 671 lab-confirmed cases) and 23 deaths were reported, resulting in a case-fatality ratio of 0.28 percent. The outbreak was successfully contained through the implementation of coordinated, multisectoral prevention and control strategies, supported by both national and international stakeholders. The cholera vaccine campaign with one-dose strategy was started in November 2022. The proportion of vaccinated people among the target population evolved from 4.8% in November 2022, to 30.6% in December 2022, 34.2% in January 2023 and 45.3% in February 2023. This paper describes the epidemiology of cholera outbreak in Lebanon and summarises outbreak response in the context of a humanitarian emergency.

The covid-19 pandemic saw frequent changes and conflicts in mask policies and politicization of masks. On reviewing the evidence, including studies published after the pandemic, the data suggest respirators are more effective than masks in healthcare, but must be continuously worn to be protective. Healthcare and aged care settings amplify outbreaks, so protection of patients and staff is paramount. Most guidelines assume risk is only present during close contact or aerosol generating procedures, but studies show intermittent use of respirators is not protective. New research in aerosol science confirms the risk of infection is widespread in health facilities. In community settings, any mask use is protective during epidemics, especially if used early, when combined with hand hygiene, and if wearers are compliant. Community use of N95 respirators is more protective than surgical masks, which are more protective than cloth masks, but even cloth masks provide some protection. Mask guidelines should be adaptable to the specific context and should account for rising epidemic activity, and whether a pathogen has asymptomatic transmission. The main rationale for universal masking during pandemics is asymptomatic transmission, which means risk of transmission cannot be self-identified. The precautionary principle should be applied during serious emerging infections or pandemics when transmission mode is not fully understood, or vaccines and drugs are not available. If respirators are not available, medical or cloth masks could be used as a last resort. Data exist to support extended use and reuse of masks and respirators during short supply. In summary, extensive evidence generated during the covid-19 pandemic confirms the superiority of respirators and supports the use of masks and respirators in the community during periods of high epidemic activity. Some gaps in research remain, including economic analyses, research in special population groups for whom masking is challenging, and research on countering disinformation.

Introduction: Compromised neonatal intensive care unit neonates are at risk of acquiring late-onset infections (late-onset sepsis [LOS]). Neonates born with congenital anomalies (CAs) could have an additional LOS risk. Methods: Utilising the population-based Australian and New Zealand Neonatal Network data from 2007 to 2017, bacterial LOS rates were determined in very preterm (VPT, <32 week), moderately preterm (MPT, 32–36 weeks), and term (FT, 37–41 weeks) neonates with or without CA. Stratified by major surgery, the association between CA and bacterial LOS was evaluated. Results: Of 102,808 neonates, 37.7%, 32.8%, and 29.6% were born VPT, MPT, and FT, respectively. Among these, 3.4% VPT, 7.5% MPT, and 16.2% FT neonates had CA. VPT neonates had the highest LOS rate (11.1%), compared to MPT (1.8%) and FT (1.8%) neonates. LOS rates were higher in CA neonates than those without (8.2% versus 5.1% adjusted relative risk [aRR] 1.67, 95% confidence interval [CI]: 1.45–1.92). Neonates with surgery had a higher LOS rate (14.2%) than neonates without surgery (4.4%, p < 0.001). Among the neonates without surgery, CA neonates had consistently higher LOS rates than those without CA (VPT 14.3% vs. 9.6% [aRR 1.32, 95% CI: 1.11–1.57]; MPT 4% vs. 0.9% [aRR 4.45, 95% CI: 3.23–6.14]; and FT 2% vs. 0.7% [aRR 2.87, 95% CI: 1.97–4.18]). For the neonates with surgery, CAs were not associated with additional LOS risks. Conclusion: Overall, we reported higher rates of LOS in neonates with CA compared to those without CA. Regardless of gestation, CA was associated with an increased LOS risk among non-surgical neonates. Optimisation of infection prevention strategies for CA neonates should be explored. Future studies are needed to evaluate if the infection risk is caused by CA or associated complications.

SUMMARY: This narrative review and meta-analysis summarizes a broad evidence base on the benefits—and also the practicalities, disbenefits, harms and personal, sociocultural and environmental impacts—of masks and masking. Our synthesis of evidence from over 100 published reviews and selected primary studies, including re-analyzing contested meta-analyses of key clinical trials, produced seven key findings. First, there is strong and consistent evidence for airborne transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other respiratory pathogens. Second, masks are, if correctly and consistently worn, effective in reducing transmission of respiratory diseases and show a dose-response effect. Third, respirators are significantly more effective than medical or cloth masks. Fourth, mask mandates are, overall, effective in reducing community transmission of respiratory pathogens. Fifth, masks are important sociocultural symbols; non-adherence to masking is sometimes linked to political and ideological beliefs and to widely circulated mis- or disinformation. Sixth, while there is much evidence that masks are not generally harmful to the general population, masking may be relatively contraindicated in individuals with certain medical conditions, who may require exemption. Furthermore, certain groups (notably D/deaf people) are disadvantaged when others are masked. Finally, there are risks to the environment from single-use masks and respirators. We propose an agenda for future research, including improved characterization of the situations in which masking should be recommended or mandated; attention to comfort and acceptability; generalized and disability-focused communication support in settings where masks are worn; and development and testing of novel materials and designs for improved filtration, breathability, and environmental impact.

Background: As the COVID-19 pandemic began, cases of respiratory illness of unknown cause could have presented early disease signals. The detection of such signals can provide useful clues regarding disease emergence and opportunities for early outbreak control. This study assessed trends in the global incidence of reports of respiratory illness of unknown cause as early indicators of COVID-19 in late 2019, using the early warning system, EPIWATCH, to investigate the disease’s origins and early epidemiology. Methods: Global news articles published between 1-Oct and 31-Dec in 2019 and collected by EPIWATCH, an open-source Artificial Intelligence (AI)-driven epidemic surveillance system, were searched for keywords relating to unknown respiratory illness. Control periods representing the pre-COVID period (1-Oct to 31-Dec 2016-2018) were used to compare report trends over time. Data on report location, case demographics, outbreak setting, and type of illness, were extracted and descriptively analysed. Fisher’s exact tests were conducted to assess proportional differences between years. Results: Overall, 113 EPIWATCH reports of unknown respiratory illness were identified from 12 countries in 2019. Most reports (n=111 [98.2%]) were published in Northern hemisphere countries, in particular Russia (n=A72 [63.7%]) and the United States (n=17 [15.0%]). China experienced a month-on-month increase in reports. Schools were the most reported outbreak setting (n=49 [43.4%]). The proportion of included reports in 2019 was significantly higher compared to 2016-2018 (p<.001). Conclusion: Potential early COVID-19 signals were detected from various countries before the end of 2019. AI-driven open-source disease surveillance systems, such as EPIWATCH, can provide early warnings to enhance disease surveillance and improve outbreak prevention and response.