Resurgence of Diphtheria in North Kerala, India, 2016: Laboratory Supported Case-Based Surveillance Outcomes

Abstract

introduction: As part of national program, laboratory supported vaccine preventable diseases surveillance was initiated in Kerala in 2015. Mechanisms have been strengthened for case investigation, reporting, and data management. Specimens collected and sent to state and reference laboratories for confirmation and molecular surveillance. The major objective of this study is to understand the epidemiological information generated through surveillance system and its utilization for action.Methods: Surveillance data captured from reporting register, case investigation forms, and laboratory reports was analyzed. Cases were allotted unique ID and no personal identifying information was used for analysis. Throat swabs were collected from investigated cases as part of surveillance system. All Corynebacterium diphtheriae isolates were confirmed with standard biochemical tests, ELEK's test, and real-time PCR. Isolates were characterized using whole genome-based multi locus sequence typing method. Case investigation forms and laboratory results were recorded electronically. Public health response by government was also reviewed.results: A total of 533 cases were identified in 11 districts of Kerala in 2016, of which 92% occurred in 3 districts of north Kerala; Malappuram, Kozhikode, and Kannur. Almost 79% cases occurred in >10 years age group. In <18 years age group, 62% were male while in ≥18 years, 69% were females. In <10 years age group, 31% children had received three doses of diphtheria vaccine, whereas in ≥10 years, 3% cases had received all doses. Fifteen toxigenic C. diphtheriae isolates represented 6 novel sequence types (STs) . Other STs observed are ST-50, ST-295, and ST-377.conclusion: Diphtheria being an emerging pathogen, establishing quality surveillance for providing real-time information on disease occurrence and mortality is imperative. The epidemiological data thus generated was used for targeted interventions and to 2 Sangal et al.

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“…The study is important for understanding the emergence of outbreaks (Seth-Smith and Egli 2019). For now, nextgeneration sequencing (NGS) technologies can also result in comprehensive data of pathogens, including virulent factors, drug resistance, toxin, and other genomic sequences contributing to diphtheria outbreaks (Trost et al 2012;Sangal et al 2017).…”