Geographic Pattern of Typhoid Fever in India: A Model-Based Estimate of Cohort and Surveillance Data

Characterising global antimicrobial resistance research explains why One Health solutions are slow in development: An application of AI-based gap analysis

The global health crisis posed by increasing antimicrobial resistance (AMR) implicitly requires solutions based a One Health approach, yet multisectoral, multidisciplinary research on AMR is rare and huge knowledge gaps exist to guide integrated action. This is partly because a comprehensive survey of past research activity has never performed due to the massive scale and diversity of published information. Here we compiled 254,738 articles on AMR using Artificial Intelligence (AI; i.e., Natural Language Processing, NLP) methods to create a database and information retrieval system for knowledge extraction on research perfomed over the last 20 years. Global maps were created that describe regional, methodological, and sectoral AMR research activities that confirm limited intersectoral research has been performed, which is key to guiding science-informed policy solutions to AMR, especially in low-income countries (LICs). Further, we show greater harmonisation in research methods across sectors and regions is urgently needed. For example, differences in analytical methods used among sectors in AMR research, such as employing culture-based versus genomic methods, results in poor communication between sectors and partially explains why One Health-based solutions are not ensuing. Therefore, our analysis suggest that performing culture-based and genomic AMR analysis in tandem in all sectors is crucial for data integration and holistic One Health solutions. Finally, increased investment in capacity development in LICs should be prioritised as they are places where the AMR burden is often greatest. Our open-access database and AI methodology can be used to further develop, disseminate, and create new tools and practices for AMR knowledge and information sharing.

A unique case of Salmonella typhi peritonitis in a CAPD patient

Peritonitis is the Achilles heel of continuous ambulatory peritoneal dialysis (CAPD) leading to significant morbidity and mortality. We report a 57 year old lady with coronary artery disease, pulmonary hypertension and diabetic kidney disease on CAPD for four years, who presented with Salmonella typhi peritonitis. As response to intraperitoneal antibiotics was unsatisfactory, the peritoneal dialysis catheter was removed after five days and shifted to maintenance hemodialysis. Following resolution of infection after a prolonged course of intravenous antibiotics, a swan neck catheter was re-implanted after eight weeks. There was peritoneal membrane failure and hence she continued on hemodialysis but she succumbed.

Assessing the global risk of typhoid outbreaks caused by extensively drug resistant Salmonella Typhi

Since its emergence in 2016, extensively drug resistant (XDR) Salmonella enterica serovar Typhi (S. Typhi) has become the dominant cause of typhoid fever in Pakistan. The establishment of sustained XDR S. Typhi transmission in other countries represents a major public health threat. We show that the annual volume of air travel from Pakistan strongly discriminates between countries that have and have not imported XDR S. Typhi in the past, and identify a significant association between air travel volume and the rate of between-country movement of the H58 haplotype of S. Typhi from fitted phylogeographic models. Applying these insights, we analyze flight itinerary data cross-referenced with model-based estimates of typhoid fever incidence to identify the countries at highest risk of importation and sustained onward transmission of XDR S. Typhi. Future outbreaks of XDR typhoid are most likely to occur in countries that can support efficient local S. Typhi transmission and have strong travel links to regions with ongoing XDR typhoid outbreaks (currently Pakistan). Public health activities to track and mitigate the spread of XDR S. Typhi should be prioritized in these countries.

Mapping the stability of febrile illness hotspots in Punjab from 2012 to 2019- a spatial clustering and regression analysis

INTRODUCTION

Febrile illnesses (FI) represent a typical spectrum of diseases in low-resource settings, either in isolation or with other common symptoms. They contribute substantially to morbidity and mortality in India. The primary objective was to study the burden of FI based on Integrated Disease Surveillance Programme (IDSP) data in Punjab, analyze geospatial and temporal trends and patterns, and identify the potential hotspots for effective intervention.

METHODS

A retrospective ecological study used the district-level IDSP reports between 2012 and 2019. Diseases responsible for FI on a large scale, like Dengue, Chikungunya, Malaria (Plasmodium Falciparum, P. Vivax), Enteric fever, and Pyrexia of Unknown Origin (PUO), were included in the analysis. The digital map of Punjab was obtained from GitHub. Spatial autocorrelation and cluster analysis were done using Moran's I and Getis-Ord G* to determine hotspots of FI using the incidence and crude disease numbers reported under IDSP. Further, negative binomial regression was used to determine the association between Spatio-temporal and population variables per the census 2011. Stable hotspots were depicted using heat maps generated from district-wise yearly data.

RESULTS

PUO was the highest reported FI. We observed a rising trend in the incidence of Dengue, Chikungunya, and Enteric fever, which depicted occasional spikes during the study period. FI expressed significant inter-district variations and clustering during the start of the study period, with more dispersion in the latter part of the study period. P.Vivax malaria depicted stable hotspots in southern districts of Punjab. In contrast, P. Falciparum malaria, Chikungunya, and PUO expressed no spatial patterns. Enteric Fever incidence was high in central and northeastern districts but depicted no stable spatial patterns. Certain districts were common incidence hotspots for multiple diseases. The number of cases in each district has shown over-dispersion for each disease and has little dependence on population, gender, or residence as per regression analysis.

CONCLUSIONS

The study demonstrates that information obtained through IDSP can describe the spatial epidemiology of FI at crude spatial scales and drive concerted efforts against FI by identifying actionable points.

Comparison of Strategies for Typhoid Conjugate Vaccine Introduction in India: A Cost-Effectiveness Modeling Study

Background

Typhoid fever causes substantial global mortality, with almost half occurring in India. New typhoid vaccines are highly effective and recommended by the World Health Organization for high-burden settings. There is a need to determine whether and which typhoid vaccine strategies should be implemented in India.

Methods

We assessed typhoid vaccination using a dynamic compartmental model, parameterized by and calibrated to disease and costing data from a recent multisite surveillance study in India. We modeled routine and 1-time campaign strategies that target different ages and settings. The primary outcome was cost-effectiveness, measured by incremental cost-effectiveness ratios (ICERs) benchmarked against India’s gross national income per capita (US$2130).

Results

Both routine and campaign vaccination strategies were cost-saving compared to the status quo, due to averted costs of illness. The preferred strategy was a nationwide community-based catchup campaign targeting children aged 1–15 years alongside routine vaccination, with an ICER of $929 per disability-adjusted life-year averted. Over the first 10 years of implementation, vaccination could avert 21–39 million cases and save $1.6–$2.2 billion. These findings were broadly consistent across willingness-to-pay thresholds, epidemiologic settings, and model input distributions.

Conclusions

Despite high initial costs, routine and campaign typhoid vaccination in India could substantially reduce mortality and was highly cost-effective.