Chikungunya in Indonesia: Epidemiology and diagnostic challenges

Abstract

Background: Chikungunya virus (CHIKV) is often overlooked as an etiology of fever in tropical and sub-tropical regions. Lack of diagnostic testing capacity in these areas combined with co-circulation of clinically similar pathogens such as dengue virus (DENV), hinders CHIKV diagnosis. To better address CHIKV in Indonesia, an improved understanding of epidemiology, clinical presentation, and diagnostic approaches is needed.

Methodology/principal findings: Acutely hospitalized febrile patients ≥1-year-old were enrolled in a multi-site observational cohort study conducted in Indonesia from 2013 to 2016. Demographic and clinical data were collected at enrollment; blood specimens were collected at enrollment, once during days 14 to 28, and three months after enrollment. Plasma samples negative for DENV by serology and/or molecular assays were screened for evidence of acute CHIKV infection (ACI) by serology and molecular assays. To address the co-infection of DENV and CHIKV, DENV cases were selected randomly to be screened for evidence of ACI. ACI was confirmed in 40/1,089 (3.7%) screened subjects, all of whom were DENV negative. All 40 cases initially received other diagnoses, most commonly dengue fever, typhoid fever, and leptospirosis. ACI was found at five of the seven study cities, though evidence of prior CHIKV exposure was observed in 25.2% to 45.9% of subjects across sites. All subjects were assessed during hospitalization as mildly or moderately ill, consistent with the Asian genotype of CHIKV. Subjects with ACI had clinical presentations that overlapped with other common syndromes, atypical manifestations of disease, or persistent or false-positive IgM against Salmonella Typhi. Two of the 40 cases were possibly secondary ACI.

Conclusions/significance: CHIKV remains an underdiagnosed acute febrile illness in Indonesia. Public health measures should support development of CHIKV diagnostic capacity. Improved access to point-of-care diagnostic tests and clinical training on presentations of ACI will facilitate appropriate case management such as avoiding unneccessary treatments or antibiotics, early response to control mosquito population and eventually reducing disease transmission.

Fig 1. Study algorithm to identify acute chikungunya infection.

*DENV IgM/IgG, NS1, RT-PCR; ** CHIKV IgM/IgG, RT-PCR.

Fig 2. The distribution of Chikungunya virus exposure in Indonesia.

Acute CHIKV infection (ACI): CHIKV RNA was detected by rRT-PCR and/or sero-conversion or four-fold increase in OD ratio of IgM and IgG between paired samples was observed; Previous infection: no evidence of ACI, IgG was positive in acute specimens; No exposure of CHIKV: IgG was negative in convalescent specimens. Map source Wikimedia Commons Atlas of the World [Atlas of Indonesia]. Available from: https://commons.wikimedia.org/wiki/Atlas_of_Indonesia#/media/File:Map_of_Indonesia_Demis.png [Accessed 21 October 2019].

Fig 3. Distribution of acute chikungunya infection cases by month and year.

Fig 4. Phylogenetic trees showing the relationship of Chikungunya virus identified in AFIRE study.

The relationship was constructed by the maximum likelihood method using nucleotide sequences of the E1 gene (1320 bp) with 1000 bootstrap replicates. The trees consist of 30 E1 gene nucleotide sequences from AFIRE specimens and other sequences from GenBank database. The AFIRE specimens are shown in bold, in the following format: Subject Identification Number | Country | City | Year. The sequences retrieved from GenBank are shown in the following format: Accession Number | Strain (if available) | Country | City (if available) | Year. The scale presents the number of nucleotide substitutions per site along the branches. The sequences of the AFIRE Chikungunya E1 gene were submitted to GenBank. The genotypes were inferred based on phylogenetic clustering set by authors referred for the analysis.