BMC Infectious Diseases

BackgroundLittle is known about the relationship between weight gain during treatment and the subsequent risk of cardiovascular and metabolic (cardiometabolic) diseases. We assessed the relationship between changes in body mass index (BMI) during TB treatment with prevalence post-TB metabolic syndrome, a strong predictor of cardiometabolic diseases. MethodsWe enrolled a prospective cohort of individuals successfully treated for TB disease in Tbilisi, Georgia, from 2019 - 2022. Eligible participants were HIV-negative individuals aged [&ge;]16 years with newly diagnosed and laboratory-confirmed pulmonary TB. Our study exposure was the relative change in BMI from treatment initiation to treatment completion, dichotomized using [&ge;]5% relative increase cut-off. Our primary study outcome was prevalence post-TB metabolic syndrome (i.e., having [&ge;]3 of the following: elevated blood pressure, elevated triglycerides, low high-density lipoprotein, elevated glycated hemoglobin [HbA1c], and abdominal obesity) at any study visits (including the end of, 6- and 12-months post-TB treatment). Multilevel models were used to estimate the effect of BMI change on post-TB metabolic syndrome. ResultsAmong 120 participants, the adjusted risk of having metabolic syndrome after TB treatment among those with [&ge;]5% relative increase in BMI was 2.07 times (95% confidence interval [CI] 1.07-4.01) the risk of those with <5% relative increase in BMI during treatment. Additionally, the adjusted mean of post-TB HbA1c among those with [&ge;]5% relative increase in BMI was 0.37 (95%CI 0.03-0.71) points higher compared to those with <5% relative increase in BMI. ConclusionsOur findings indicate that weight gain during TB treatment may influence the risk of cardiovascular/metabolic diseases after TB treatment. Key points summaryIn a cohort of persons successfully treated for pulmonary tuberculosis, nearly half had [&ge;]5% BMI increase during treatment. Notably, those with [&ge;]5% BMI increase had higher glycated hemoglobin levels and were twice as likely to have metabolic syndrome after tuberculosis treatment completion.

BackgroundIntensive screening and testing for COVID-19 could facilitate early detection and isolation of infected persons and thereby control the size of the epidemic. It could also facilitate earlier and more targeted therapy. These factors could plausibly reduce attributable mortality which was the hypothesis tested in this study. MethodsLinear regression was used to assess the country-level association between COVID-19 attributable mortality per 100 000 inhabitants (mortality/capita) and COVID-19 tests/capita (number of tests/100 000 inhabitants) controlling for the cumulative number of COVID-19 infections/100 000 inhabitants (cases/capita), the age of the epidemic (number of days between first case reported and 8 April), national health expenditure per capita and WHO world region. ResultsThe COVID-19 mortality rate varied between 0.3 and 3110 deaths/100 000 inhabitants (median 30, IQR 8-105). The intensity of testing per 100 000 also varied considerably (median 21,970, IQR 2,735-89,095) as did the number of COVID-19 cases per 100 000 (median 1,600, IQR 340-4,760 cases/100 000). In the multivariate model, the COVID-19 mortality rate was negatively associated with tests/capita (Coef. -0.036, 95% CI -0.047- -0.025) and positively associated with cases/capita (Coef. 0.093, 95% CI 0.819- 1.034). ConclusionsThe results are compatible with the hypothesis that intensive testing and isolation could play a role in reducing COVID-10 mortality rates.

BackgroundAngiotensin Converting Enzyme Inhibitors (ACEi) and Angiotensin Receptor Blockers (ARB) have anti-inflammatory properties via decreasing AT1R binding/levels, reducing Reactive Oxygen Species (ROS) and cytokine activation. This study investigated whether these medications can negatively impact hemagglutination inhibition (HAI) responses to influenza vaccination. MethodsParticipants, over the age of 18, were consented and enrolled in the study to receive an influenza vaccine during the 2024-2025 influenza season. Participants were classified into individuals on either ACEi or ARB. Healthy controls were selected based on age-sex-body mass index (BMI) matching and a second control group of participants were diagnosed with hypertension (HTN). but on taking these medications. Analysis focused on relative risk ratios (RR) for seroconversion to the influenza vaccine, in addition to day 28 geometric mean titers (GMT), number of seroprotected participants, and fold change was carried out. ResultsWe observed a lower trend of seroconversion amongst participants taking either medication compared to the HTN controls and did not observe any differences compared to the healthy controls. There were no differences in day 28 GMT, although the HTN controls had statistically significant higher fold changes in HAI titers compared to the healthy controls. Compared to the treatment groups, the HTN controls had a non-significant higher fold change against all three strains included in the influenza vaccine. ConclusionsOverall, the use of medications did not impact seroconversion when compared to healthy controls, but participants did have a lower trend for seroconversion compared to the HTN controls. This could be due to reduced inflammatory markers in people taking these medications, but this reduction in titer is similar to that in healthy participants. More studies comparing inflammatory markers related to medications in people are needed. In addition, determining the impact of the use of ACEi and ARB on lymphocyte responses is critical for effective influenza vaccination strategies.

BackgroundScrub typhus is an infectious disease that affects multiple organs. However, the long-term cardiovascular (CV) risk in survivors remains unknown. MethodA retrospective cohort study used administrative claims data from the National Health Insurance Research Database (NHIRD) to investigate the CV risk of scrub typhus survivors from January 1, 2010, to December 31, 2015. People who had prior CV events before the diagnosis of scrub typhus were excluded. The CV outcomes of interest were acute myocardial infarction (AMI), heart failure hospitalization (HFH), hemorrhagic or ischemic stroke, new-onset atrial fibrillation (AF), aneurysm or dissection of aorta, venous thromboembolism (VTE), and CV death. ResultA total of 2,269 patients with scrub typhus and without a prior CV event were identified (mean age 47.8{+/-}16.1 years, 38.0% female). The health control cohort (n=2,264) was selected to compare by the frequency matching with age, gender, and co-morbidities with patients with scrub typhus. The incidence of HFH, new-onset AF, and total events was significantly higher among patients with scrub typhus than the control cohort with an adjusted hazard ratio (aHR) of 1.97, 95% confidence interval (CI) 1.13-3.42 for HFH; 2.48, 95% CI: 1.23-5.0 for new-onset AF; 1.43, 95% CI: 1.08-1.91 for total CV events, respectively. The event rates of other outcomes were similar between the two groups. ConclusionIn the cohort study, survivors of scrub typhus are at heightened risk of subsequent CV events, especially for HFH and new-onset AF. These findings serve as an important reminder to physicians regarding the significant CV risk that remains present following acute scrub typhus infection.

BackgroundTuberculosis (TB) is a major public health concern, particularly among people living with the Human immunodeficiency Virus (PLWH). Accurate prediction of TB disease in this population is crucial for early diagnosis and effective treatment. Logistic regression and regularized machine learning methods have been used to predict TB, but their comparative performance in HIV patients remains unclear. The study aims to compare the predictive performance of logistic regression with that of regularized machine learning methods for TB disease in HIV patients. MethodsRetrospective analysis of data from HIV patients diagnosed with TB in three hospitals in Kisumu County (JOOTRH, Kisumu sub-county hospital, Lumumba health center) between [dates]. Logistic regression, Lasso, Ridge, Elastic net regression were used to develop predictive models for TB disease. Model performance was evaluated using accuracy, and area under the receiver operating characteristic curve (AUC-ROC). ResultsOf the 927 PLWH included in the study, 107 (12.6%) were diagnosed with TB. Being in WHO disease stage III/IV (aOR: 7.13; 95%CI: 3.86-13.33) and having a cough in the last 4 weeks (aOR: 2.34;95%CI: 1.43-3.89) were significant associated with the TB. Logistic regression achieved accuracy of 0.868, and AUC-ROC of 0.744. Elastic net regression also showed good predictive performance with accuracy, and AUC-ROC values of 0.874 and 0.762, respectively. ConclusionsOur results suggest that logistic regression, Lasso, Ridge regression, and Elastic net can all be effective methods for predicting TB disease in HIV patients. These findings may have important implications for the development of accurate and reliable models for TB prediction in HIV patients.

ObjectiveThe detection of communicable pathogens responsible for major outbreaks relies on health care professionals recognition of symptoms manifesting in infectious individuals. Early warning of such communicable diseases before the onset of symptoms could improve both patient care and public health responses. However, the potential impact of such a host-based early warning system on containing the spread of an outbreak and in steering public health response is unknown. MethodsWe extend the deterministic SEIR (Susceptible, Exposed, Infectious, Recovered) model to simulate disease outbreak scenarios and to quantify the potential impact of a host-based early warning capability to mitigate pathogen transmission during an outbreak. In particular, we compare and contrast the performance of five different policies: Self-monitoring and reporting (baseline SEIR model), Quarantining the entire population, Quarantine-on-alert (with high sensitivity early warning), Quarantine-on-alert (with high specificity early warning), and Quarantine-on-alert (ideal early warning). We further evaluate these five policy options against four different outbreak scenarios with high or low disease transmission and high or low initial population exposures. ResultsFor all scenarios, a quarantine-on-alert policy coupled with the near-ideal early warning capability reduces quarantine needs with only a small increase in the number of additional infections. The cost of a highly specific early detection system (i.e., a reduction in false alarms and thus quarantine costs) is an increase in additional infections relative to the near-ideal system. Conversely, a highly sensitive early detection system increases the percentage of the population in quarantine compared to both the ideal and high-specificity early detection system while also reducing the number of additional infections to nearly the numbers seen by quarantining the entire population a priori. ConclusionsOur simulations demonstrate the utility of host-based early warning systems in controlling an outbreak under various outbreak conditions. Our tools also provide a simulation capability for evaluating public health policies enabling quantitative evaluation of their impacts prior to implementation.

Backgroundcontroversy has arisen in the scientific community on whether the use of renin angiotensin system (RAS) inhibitors in the context of COVID-19 would be of benefit or harmful. A meta-analysis of eligible studies comparing the occurrence of severe and fatal COVID-19 in infected patients who were under treatment with angiotensin converting enzyme inhibitors (ACEI) or angiotensin receptor blockers (ARB) vs no treatment or other antihypertensives was conducted. MethodsPubMed, Google Scholar, the Cochrane Library, MedRxiv and BioRxiv were searched for relevant studies. Fixed-effect models or random-effect models were used depending on the heterogeneity between estimates. Resultsa total of fifteen studies with 21,614 patients were included. The use of RAS inhibitors was associated with a non-significant 20% decreased risk of the composite outcome (death, admission to intensive care unit, mechanical ventilation requirement or progression to severe or critical pneumonia): RR 0.81 (95%CI: 0.631.04), p=0.10, I2=82%. In a subgroup analysis that included hypertensive subjects only, ACEI/ARB were associated with a 27% significant decrease in the risk of the composite outcome (RR 0.73 (95%CI: 0.56 0.96), p=0.02, I2=65%). Conclusionthe results of this pooled analysis suggest that the use of ACEI/ARB does not worsen the prognosis, and could even be protective in hypertensive subjects. Patients should continue these drugs during their COVID-19 illness.

BackgroundFamily-based HIV index case testing identifies family members with unknown HIV status and links them to care. Data are limited in southern Ethiopia. MethodsA facility-based cross-sectional study was conducted among 377 adults on antiretroviral therapy (ART) in Wolaita Zone, Southern Ethiopia, from November 2022 to May 2023. Participants were selected using systematic random sampling. Data were collected via interviewer-administered semi-structured questionnaire. Multivariable logistic regression identified factors associated with index case family testing. Adjusted odds ratios (AOR) with 95% confidence intervals (CI) were calculated, and statistical significance was declared at p < 0.05. ResultsThe proportion of index case family testing for HIV was 84.9% (95% CI: 81.2- 88.6). In multivariable analysis, urban residence (AOR = 2.8; 95% CI: 1.16-6.75), duration on ART greater than 12 months (AOR = 13.0; 95% CI: 4.6-36.9), disclosure of HIV status to family members (AOR = 5.6; 95% CI: 1.9-16.5), discussion of HIV status with family members (AOR = 6.6; 95% CI: 1.9-23.2), and being counselled by health professionals to bring families for testing (AOR = 6.3; 95% CI: 2.1-19.0) were significantly associated with index case family testing. ConclusionThe prevalence of family-based HIV index case testing in Wolaita Zone was 84.9%, below the national 95% target. Health professionals should strengthen counselling on ART adherence, status disclosure, family discussion, and active referral to improve testing uptake among family members of people living with HIV.

BackgroundDigital traces from social media and online search platforms have been used to support infectious disease forecasting, but their performance during the COVID-19 pandemic has varied widely. It is still uncertain which types of digital signals add dependable information to established forecasting models. ObjectiveThis study evaluated whether Twitter indicators and Google symptom search trends improve forecasts of COVID-19 cases in the United States. A second goal was to examine whether any gains remain consistent across two different forecasting approaches, Prophet and SARIMAX. MethodsNational daily COVID-19 case data were linked with Twitter-based emotion and Google Trends symptom variables. A forward-selection procedure identified the strongest predictors from each source. Four Prophet models were trained and tested through rolling 30-day forecasts. The same predictor sets were then used in parallel SARIMAX models. Performance was assessed using RMSE, MAE, and MAPE, and results were inspected across major epidemic waves. ResultsTwitter indicators produced the clearest and most consistent improvements. In the Prophet models, the Twitter-enhanced version reduced 30-day forecast error by about 14% compared with the baseline. Google symptom searches showed smaller and less stable improvements, and combining Google trends with Twitter signals did not produce additional benefits. SARIMAX models showed the same general pattern, although improvements were more modest. Across epidemic waves, Twitter-based models reacted more quickly to shifts in transmission than the baseline model. ConclusionsTwitter emotion indicators, especially neutral and informational posts, provided meaningful forecasting value across models and horizons. Google symptom searches contributed far less and did not strengthen performance when added to the Twitter predictors. The consistency of the findings across two modeling frameworks suggests that social media activity can offer reliable supplemental information for real-time epidemic forecasting. Continued work is needed to understand how these signals behave at finer spatial scales and in future outbreaks.

BackgroundNarrative descriptions of HIV and Trypanosoma cruzi, the causative agent of Chagas disease, co-infection exist in the literature but the breadth and depth of the data underlying these descriptions has not been previously thoroughly scrutinised and reactivation is poorly understood. The aim of this systematic review was to identify, synthesise and analyse the published literature on the epidemiology and clinical features of T. cruzi and HIV co-infection. MethodsA systematic review of published literature on HIV and T. cruzi co-infection was conducted. Six international databases were searched: Medline, Embase, Global Health, Global Index Medicus, Web of Science and Scopus. Articles reporting on HIV and Trypanosoma cruzi co-infection, as defined by the authors, with no restrictions on study type, language or date of publication or reporting were included. Results152 articles (62% case reports or series) were included which reported on 1,603 individuals with co-infection and 225 with presumed reactivation. Reported prevalence of co-infection varied greatly by region and setting of screening, from 0.1 to 1% in unselected populations, and was particularly high when screening inpatients known to have HIV for T. cruzi infection (26-48%). 83% of reactivations were reported in individuals with CD4<200 cells/mm3. CNS reactivation, typically presenting with meningoencephalitis and/or cerebral lesions, accounted for 68% of all published cases of reactivation. Myocarditis (accounting for 9% published reactivation cases) was less well characterised. Mortality of all reactivation cases was 59% (77% in those with CNS reactivation). ConclusionT. cruzi reactivation mainly affects those with untreated HIV and lower CD4 counts. CNS reactivation is the most common clinical picture and confers high mortality. Prompt recognition of reactivation and immediate initiation of trypanocidal therapy (with benznidazole or nifurtimox) is recommended. Increased education and better awareness of the risks of co-infection are needed, as is systematic screening of individuals at-risk.

BackgroundIndividuals with advanced HIV disease (AHD) have a heightened risk of mortality despite access to antiretroviral therapy (ART). Sub-Saharan Africa (SSA) has a disproportionate burden of AHD-associated deaths. However, there is limited country-specific data on AHDs burden and associated risk factors to help design targeted interventions. Therefore, this study determined the prevalence and factors associated with AHD among ART-naive and ART-experienced adults with HIV at five AIDS Healthcare Foundation (AHF)-supported facilities in Zambia. MethodologyWe conducted a cross-sectional study among 231 ART-naive and ART-experienced people living with HIV (PLHIV) and collected demographic and clinical data using a structured questionnaire. The primary outcome was AHD, defined as a CD4 count less than 200 cells/{micro}L using the VISITECT(R) CD4 point-of-care test. Multivariable logistic regression was used to assess factors associated with AHD. ResultsAmong the study participants, 59.7% were female, and 54% were aged 19-35 years. Most participants were ART-naive (79.2%), with 85.3% classified in WHO clinical stage 1. The prevalence of AHD was 47.6% (110/231), significantly higher among ART-naive participants [51.9% (95/183)] compared to ART-experienced participants [31.2% (15/48), p=0.011]. ART-naive participants aged 19-35 years exhibited a notably higher prevalence of AHD (51.6%) compared to those aged 13-18, 36-45, and >45 years (5.3%, 34.7%, and 8.4%, respectively) and had significantly higher baseline viral load values (25,000 copies/mL vs. 9,690 copies/mL, p=0.037). Additionally, among ART-naive participants, a significantly higher proportion of individuals in WHO stages 2, 3, and 4 had AHD compared to those without AHD. Across all participants, the factors significantly associated with AHD included anemia (adjusted odds ratio [aOR] 3.03, 95% confidence interval [CI]: 1.15-7.97) and being from the New Masala Clinic health facility (aOR 3.79, 95% CI: 1.17-12.30) ConclusionAdvanced HIV disease was prevalent, particularly among ART-naive individuals, and it was significantly associated with anemia and health facility location. There is a need for formulation of interventions, especially among ART-naive PLHIV who are anemic. Additionally, studies to integrate point-of-care diagnostics such as the VISITECT(R) CD4 test into routine HIV care be conducted in resource-limited settings are warranted for early detection of AHD.

BackgroundThe contribution of various enteropathogens to the occurrence of acute gastroenteritis (AGE) remains uncertain in highly endemic settings. We describe the frequency of norovirus-only detections and norovirus co-detections in hospitalized patients in Bangladesh and compare their clinical severity and viral load. MethodsFrom March 2018-October 2021, 1,250 AGE cases and 1,250 non-AGE controls of all ages were enrolled at 10 tertiary care hospitals in Bangladesh. All norovirus-positive AGE cases (n=111) and non-AGE controls (n=182), and a randomly selected subset of 126 norovirus-negative AGE cases, were tested for other enteric viral, bacterial, and parasitic co-pathogens with quantitative real-time PCR assays. We used cycle threshold (Ct)-values as a proxy for viral load and the Vesikari scale to assess disease severity. ResultsOverall, 92% (218/237) of AGE cases had [&ge;]1 enteropathogen detected. Among 293 norovirus-positive AGE cases and non-AGE controls, 88 (30%) were norovirus-only detections and 205 (70%) were norovirus co-detections. Norovirus-rotavirus was the predominant co-detection, found in 140 (68%) of 205 norovirus co-detections. No differences in clinical severity were observed among AGE cases with norovirus-only versus norovirus co-detections. The median (interquartile range) Ct-values among genogroup II norovirus-only AGE cases, norovirus co-detection AGE cases, and norovirus-positive non-AGE controls were 26 (21-31), 25 (20-29), and 25 (21-30), respectively. ConclusionsThe frequent co-detection of norovirus with other enteropathogens, especially rotavirus, along with overlapping Ct-values in patients with and without AGE, and between norovirus-only and norovirus co-detections, complicates attributing norovirus as a primary cause of AGE in hospitalized patients in Bangladesh.

AimsRenin-angiotensin system blockers such as angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) may increase the risk of adverse outcomes in COVID-19. In this study, the relationships between ACEI/ARB use and COVID-19 related mortality were examined. MethodsConsecutive patients diagnosed with COVID-19 by RT-PCR at the Hong Kong Hospital Authority between 1st January and 28th July 2020 were included. ResultsThis study included 2774 patients. The mortality rate of the COVID-19 positive group was 1.5% (n=42). Those who died had a higher median age (82.3[76.5-89.5] vs. 42.9[28.2-59.5] years old; P<0.0001), more likely to have baseline comorbidities of cardiovascular disease, diabetes mellitus, hypertension, and chronic kidney disease (P<0.0001). They were more frequently prescribed ACEI/ARBs at baseline, and steroids, lopinavir/ritonavir, ribavirin and hydroxychloroquine during admission (P<0.0001). They also had a higher white cell count, higher neutrophil count, lower platelet count, prolonged prothrombin time and activated partial thromboplastin time, higher D-dimer, troponin, lactate dehydrogenase, creatinine, alanine transaminase, aspartate transaminase and alkaline phosphatase (P<0.0001). Multivariate Cox regression showed that age, cardiovascular disease, renal disease, diabetes mellitus, the use of ACEIs/ARBs and diuretics, and various laboratory tests remained significant predictors of mortality. ConclusionsWe report that an association between ACEIs/ARBs with COVID-19 related mortality even after adjusting for cardiovascular and other comorbidities, as well as medication use. Patients with greater comorbidity burden and laboratory markers reflecting deranged clotting, renal and liver function, and increased tissue inflammation, and ACEI/ARB use have a higher mortality risk. Key PointsO_LIWe report that an association between ACEIs/ARBs with COVID-19 related mortality even after adjusting for cardiovascular and other comorbidities, as well as medication use. C_LIO_LIPatients with greater comorbidity burden and laboratory markers reflecting deranged clotting, renal and liver function, and increased tissue inflammation, and ACEI/ARB use have a higher mortality risk. C_LI

Background and ObjectiveCoronavirus disease 2019 (COVID-19) manifests as multiple clinical and pathological organ dysfunctions. It also disrupts metabolic profile due to the release of pro-inflammatory cytokines causing a systemic inflammation reaction. However, the development and correlation of dyslipidemia with acute phase reactants is unknown. This investigation was performed to assess the pathological alterations of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein (HDL), triglycerides, and total cholesterol levels in COVID-19 patients. MethodsThis was a prospective study performed on real-world patients to assess serum levels of LDL-C, HDL, TG, TC on COVID-19 patients (mild: 319; moderate: 391; critical: 357) hospitalized at our center between April 2020 through January 2021. Age- and gender-matched controls who had their lipid profiles in the same period were included as the control group. ResultsLDL-C, HDL, TG, and TC levels were significantly lower in COVID-19 patients when compared with the control group (P < 0.001, 0.047, 0.045, < 0.001, respectively). All parameters decreased gradually with COVID-19 disease severity (LDL-C: median (IQR), mild: 98 (91,134); moderate: 97 (81,113); critical: 68 (68,83); HDL: mild: 45 (37,50); moderate: 46 (41,50); critical: 40 (37,46); TG: mild: 186 (150,245); moderate: 156 (109,198); critical: 111 (98,154); TC: mild: 224 (212,238); moderate: 212 (203,213); critical: 154 (125,187)). LDL-C, TC, and TG were inversely correlated with acute phase reactants (interleukin-6 (IL-6), Procalcitonin, C-reactive protein (CRP), and D-dimers). Logistic regression demonstrated lipid profile, thyroid profile, and acute phase reactants as predictors of severity of COVID-19 disease. ConclusionHypolipidemia develops in increasing frequency with severe COVID-19 disease. It inversely correlates with levels of acute-phase reactants, indicating SARS-COV-2 as the causative agent for alteration in lipid and thyroid levels.

BackgroundChronic kidney disease (CKD) affects over 37 million adults in the United States, and people living with HIV (PLWH) are at greater risk for progression to end-stage kidney disease. Although both conditions are common among PLWH, the potential pathways through which depression and use of medications with nephrotoxic potential may influence CKD development remain underexplored. We evaluated the relationships of depression and nephrotoxic medication use with CKD prevalence among PLWH, and investigated the potential mediating effects of these factors on the pathway to CKD among PLWH. MethodsWe analyzed longitudinal data from the Multicenter AIDS Cohort Study (MACS)/Womens Interagency HIV Study (WIHS) Combined Cohort Study (MWCCS), collected between October 2018 and September 2021, to assess the prevalence of kidney dysfunction (eGFR <60 mL/min/1.73 m{superscript 2}) and its association with HIV serostatus. Generalized Estimating Equations (GEE) with a Poisson distribution and log link were used to estimate relative risks (RR) for CKD associated with HIV, depression, and other covariates. Counterfactual-based causal mediation analysis was conducted to assess whether depressive symptoms or nephrotoxic medication use partially explained the observed association between HIV and CKD. ResultsAmong 2,530 participants [1,622 PLWH and 908 people living without HIV (PLWoH)], CKD prevalence was higher in PLWH (18.1%) compared to PLWoH (9.7%). GEE analysis revealed that HIV serostatus was significantly associated with an increased risk of CKD (RR = 1.37, 95% CI: 1.28-1.48, p < 0.0001). Other significant factors included age (RR = 1.03, 95% CI: 1.03-1.03, p < 0.0001), non- Hispanic Black (RR = 1.19, 95% CI: 1.11-1.27, p < 0.0001) compared to non-Hispanic White, diabetes (RR = 1.26, 95% CI: 1.17-1.35, p < 0.0001), and higher income (RR = 0.99, 95% CI: 0.98-1.00, p = 0.005). Mediation analysis indicated that nephrotoxic medication use, accounted for a small but significant proportion of the HIV- CKD association (indirect effect OR = 1.02, 95% CI: 1.00-1.03, p = 0.02). ConclusionsWhile it is well established that PLWH have a higher prevalence of CKD compared to PLWoH, our findings suggest that nephrotoxic medication use may modestly amplify this risk. Although most of the risk appears to be attributable to the direct effects of HIV, these medications represent a modifiable contributor. PLWH receiving such treatments may benefit from closer kidney function monitoring. Future research should investigate additional psychosocial and behavioral contributors to CKD among PLWH, including depression.

Objectives: To identifiy risk factors for antimicrobial resistance (AMR) in seven pathogen-antimicrobial combinations in patients with cancer and cancer survivors. Methods: Using data from patients with recent or past cancer diagnostic codes in Oxfordshire, UK, we examined associations between 22 potential risk-factors and AMR in blood culture isolates, collected between 1-April-2015 and 31-March-2025. Results: Among 5,975 bacteraemias in 4,365 adults, we analysed 3,141 (52.6%) due to Enterobacterales and 620 (10.4%) due to Enterococcus faecalis/faecium in 2,752 patients. Fourteen risk-factors for antimicrobial-resistant bacteraemia were identified, varying across pathogen-antimicrobial combinations. Compared with no previous antimicrobial susceptibility test result, prior resistance to the same antibiotic in any culture in the last year was strongly associated with AMR across all pathogen-antimicrobial combinations (all p<=0.001). Prior antibiotic exposure and younger age were also positively associated with AMR in four and five combinations, respectively. Cancer type showed modest effects; lymphoid/haematopoietic malignancies were associated with higher odds (vs colorectal cancer) of trimethoprim-sulfamethoxazole-resistant Enterobacterales (aOR=2.07 95%CI 1.40-3.06) and vancomycin-resistant Enterococcus bacteraemia (aOR=6.68, 1.21-36.91). Conclusions: Previous resistance was the greatest risk factor for bacteraemia with AMR in cancer patients and survivors, with prior antibiotic exposure and age also contributing. Lymphoid/haematopoietic malignancies increased risk of resistance to specific antimicrobials. Keywords: antimicrobial resistance, bacteraemia, cancer, risk factors

IntroductionAnnual epidemics of respiratory synctial virus (RSV) had consistent timing and intensity between seasons prior to the SARS-CoV-2 pandemic (COVID-19). However, starting in April 2020, RSV seasonal activity declined due to COVID-19 non-pharmaceutical interventions (NPIs) before re-emerging after relaxation of NPIs. We described the unusual patterns of RSV epidemics that occurred in multiple subsequent waves following COVID-19 in different countries and explored factors associated with these patterns. MethodsWeekly cases of RSV from twenty-eight countries were obtained from the World Health Organisation and combined with data on country-level characteristics and the stringency of the COVID-19 response. Dynamic time warping and regression were used to describe epidemic characteristics, cluster time series patterns, and identify related factors. ResultsWhile the first wave of RSV epidemics following pandemic suppression exhibited unusual patterns, the second and third waves more closely resembled typical RSV patterns in many countries. Post-pandemic RSV patterns differed in their intensity and/or timing, with several broad patterns across the countries. The onset and peak timings of the first and second waves of RSV epidemics following COVID-19 suppression were earlier in the Southern Hemisphere. The second wave of RSV epidemics was also earlier with higher population density, and delayed if the intensity of the first wave was higher. More stringent NPIs were associated with lower RSV growth rate and intensity and a shorter gap between the first and second waves. ConclusionPatterns of RSV activity have largely returned to normal following successive waves in the post-pandemic era. Onset and peak timings of future epidemics following disruption of normal RSV dynamics need close monitoring to inform the delivery of preventive and control measures.

BackgroundInfectious disease modelling (IDM) is increasingly being used to understand disease transmission and inform public health policy. However, its growth and policy influence has never been quantified, possibly because of the volume of literature involved. The development of large language model (LLM)-assisted reviewing allowed us to quantify the expansion of IDM publications over time, trends in policy citations of IDM research, and regional disparities in research contributions and citations in policy documents. MethodsAn LLM-assisted bibliometric review was conducted using Embase, Medline, and Web of Science, identifying IDM publications from database inception to December 2024 using GPT-4o. Inclusion criteria encompassed peer-reviewed studies employing mathematical, statistical, or mechanistic models for infectious disease outcomes. LLM accuracy was iteratively refined by human review. We extracted publication metadata, geographic scope, and policy citations using Overton, a global database of policy documents. Growth trends were analysed using negative binomial regression models, and geographic disparities were assessed based on World Bank income classifications. ResultsA total of 33,255 IDM publications were identified over 44 years, with distinct growth phases. The LLM selection and data extraction achieved 98% and 100% accuracy respectively, compared to human search. Publication volume increased from the time of HIV/AIDS emergence, experiencing steady expansion through multiple outbreaks (Ebola, SARS, H1N1, MERS, Zika), and surged sharply just before the COVID-19 pandemic before declining post-2021. Recorded policy citations accounted for 1.7% of IDM publications, closely following the overall publication trend, peaking during periods of heightened public health attention. Policy citations largely reflected national research outputs, with notable cross-regional adoption of IDM evidence in some settings. ConclusionStrengthening the integration of IDM evidence into policymaking processes may require addressing geographic disparities in research output (and its recording in international databases), enhancing cross-regional collaboration, and improving mechanisms for policy uptake. Following the COVID-19 pandemic, policy citations declined despite continued growth in IDM literature, suggesting a potential lag or shift in policymaking priorities.

BackgroundFood insecurity has been independently associated with cholera infection and there is an inverse relationship between national food security and annual cholera incidence. However, factors that mediate increased cholera risk among food insecure households remain largely unexplored. MethodsIn a cross-sectional survey of rural households in Haiti, we explored the role of food behaviors (i.e., dietary choices and food-handling practices) as mediators of cholera risk among food-insecure families. We generated multivariable regression models to test hypothesized associations between severity of food insecurity (measured by the Household Hunger Scale), hygiene and food behaviors, and history of severe, medically-attended cholera. ResultsCompared with little to no household hunger, moderate hunger (Adjusted Odds Ratio [AOR] 1.62, 95% Confidence Interval (CI) 1.12--2.36; p=0.011) and severe hunger (AOR 2.32, 95% CI 1.27--4.22; p=0.006) were positively associated with history of severe, medically-attended cholera. Household hunger was positively associated with three behaviors: antacid use, consumption of leftover non-reheated food, and eating food and beverages prepared outside of the home (i.e., at a restaurant or from a vendor). Consumption of outside food items and antacid use were positively associated with a history of cholera. ConclusionOur findings suggest that food behaviors may mediate the association between food insecurity and cholera and contribute to an understanding of how interventions could be designed to target food insecurity as part of cholera prevention and control. Author summaryFood insecurity has been found to be a risk factor for cholera at the household and national level;[1-3] however the mechanism through which food insecurity may increase the risk of cholera remains unknown. In a large cross-sectional survey of 1072 households in rural Haiti, we observed a robust independent association between food insecurity--defined as a persistent lack of access to food in adequate quantity or quality and measured by the Household Hunger Scale--and severe, medically-attended cholera. This relationship appears to be linear, conferring a dose-dependent risk of cholera by severity of food insecurity. We found household food insecurity to be associated with three high-risk behaviors: antacid use, consumption of leftover non-reheated food, and eating food and beverages prepared outside of the home. Two high-risk behaviors--including antacid use and consumption food and beverages prepared outside of the home (i.e., at a restaurant or from a vendor)--were independent risk factors for cholera. High-risk food handling practices may be one causal pathway whereby food insecurity increases risk of cholera infection. Future longitudinal and qualitative studies should investigate whether interventions targeting food insecurity could reduce cholera risk among populations who face a high burden of both conditions.

BackgroundTuberculosis (TB) infections among children (below 15 years) is a growing concern, particularly in resource-limited settings. However, the TB burden among children is relatively unknown in Kenya where two-thirds of estimated TB cases are undiagnosed annually. Very few studies have used Autoregressive Integrated Moving Average (ARIMA), hybrid ARIMA, and Artificial Neural Networks (ANNs) models to model infectious diseases globally. We applied ARIMA, hybrid ARIMA, and Artificial Neural Network models to predict and forecast TB incidences among children in Homa bay and Turkana Counties in Kenya. MethodsThe ARIMA, ANN, and hybrid models were used to predict and forecast monthly TB cases reported in the Treatment Information from Basic Unit (TIBU) system for Homa bay and Turkana Counties between 2012 and 2021. The data were split into training data, for model development, and testing data, for model validation using an 80:20 split ratio respectively. ResultsThe hybrid ARIMA model (ARIMA-ANN) produced better predictive and forecast accuracy compared to the ARIMA (0,0,1,1,0,1,12) and NNAR (1,1,2) [12] models. Furthermore, using the Diebold-Mariano (DM) test, the predictive accuracy of NNAR (1,1,2) [12] versus ARIMA-ANN, and ARIMA-ANN versus ARIMA (0,0,1,1,0,1,12) models were significantly different, p<0.001, respectively. The 12-month forecasts showed a TB prevalence of 175 to 198 cases per 100,000 children in Homa bay and Turkana Counties in 2022. ConclusionThe hybrid (ARIMA-ANN) model produces better predictive and forecast accuracy compared to the single ARIMA and ANN models. The findings show evidence that the prevalence of TB among children below 15 years in Homa bay and Turkana Counties is significantly under-reported and is potentially higher than the national average.