METHODS: In this systematic review, meta-analysis, and modelling study, we searched PubMed, Ovid, and Web of Science for articles published from database inception until Sept 26, 2022, for prospective and retrospective cross-sectional studies that addressed serological chikungunya virus infection in any geographical region, age group, and population subgroup and for longitudinal prospective and retrospective cohort studies with data on chronic chikungunya or hospital admissions in people with chikungunya. We did a systematic review of studies on chikungunya seroprevalence and fitted catalytic models to each survey to estimate location-specific FOI (ie, the rate at which susceptible individuals acquire chikungunya infection). We performed a meta-analysis to estimate the proportion of symptomatic patients with laboratory-confirmed chikungunya who had chronic chikungunya or were admitted to hospital following infection. We used a random-effects model to assess the relationship between chronic sequelae and follow-up length using linear regression. The systematic review protocol is registered online on PROSPERO, CRD42022363102.
FINDINGS: We identified 60 studies with data on seroprevalence and chronic chikungunya symptoms done across 76 locations in 38 countries, and classified 17 (22%) of 76 locations as endemic settings and 59 (78%) as epidemic settings. The global long-term median annual FOI was 0·007 (95% uncertainty interval [UI] 0·003-0·010) and varied from 0·0001 (0·00004-0·0002) to 0·113 (0·07-0·20). The highest estimated median seroprevalence at age 10 years was in south Asia (8·0% [95% UI 6·5-9·6]), followed by Latin America and the Caribbean (7·8% [4·9-14·6]), whereas median seroprevalence was lowest in the Middle East (1·0% [0·5-1·9]). We estimated that 51% (95% CI 45-58) of people with laboratory-confirmed symptomatic chikungunya had chronic disability after infection and 4% (3-5) were admitted to hospital following infection.
INTERPRETATION: We inferred subnational heterogeneity in long-term average annual FOI and transmission dynamics and identified both endemic and epidemic settings across different countries. Brazil, Ethiopia, Malaysia, and India included both endemic and epidemic settings. Long-term average annual FOI was higher in epidemic settings than endemic settings. However, long-term cumulative incidence of chikungunya can be similar between large outbreaks in epidemic settings with a high FOI and endemic settings with a relatively low FOI.
FUNDING: International Vaccine Institute.
METHODOLOGY: A cross-sectional study involving 149 healthy adult volunteers from Tanjung Sepat was performed soon after the outbreak had subsided. All the participants donated blood samples and completed the questionnaires. Laboratory detection of anti-CHIKV IgM and IgG antibodies was performed using enzyme-linked immunoassays (ELISA). Risk factors associated with chikungunya seropositivity were determined using logistic regression.
RESULTS: The majority (72.5%, n = 108) of the study participants tested positive for CHIKV antibodies. Only 8.3% (n = 9) of the participants out of all the seropositive volunteers had an asymptomatic infection. Participants who resided with a febrile (p < 0.05, Exp(B) = 2.2, confidence interval [CI] 1.3-3.6) or a CHIKV-diagnosed person (p < 0.05, Exp(B) = 2.1, CI 1.2-3.6) in the same household were found likely to be tested positive for CHIKV antibodies.
CONCLUSIONS: Findings from the study support that asymptomatic CHIKV infections and indoor transmission occurred during the outbreak. Hence, widespread community testing and indoor use of mosquito repellent are among the possible measures that can be implemented to reduce CHIKV transmission during an outbreak.
METHODS: The residential addresses of 3054 notified CHIKV cases in 2009-2010 were georeferenced onto a base map of Sarawak with spatial data of rivers and roads using R software. The spatiotemporal spread was determined and clusters were detected using the space-time scan statistic with SaTScan.
RESULTS: Overall CHIKV incidence was 127 per 100 000 population (range, 0-1125 within districts). The average speed of spread was 70.1 km/wk, with a peak of 228 cases/wk and the basic reproduction number (R0) was 3.1. The highest age-specific incidence rate was 228 per 100 000 in adults aged 50-54 y. Significantly more cases (79.4%) lived in rural areas compared with the general population (46.2%, p<0.0001). Five CHIKV clusters were detected. Likely spread was mostly by road, but a fifth of rural cases were spread by river travel.
CONCLUSIONS: CHIKV initially spread quickly in rural areas mainly via roads, with lesser involvement of urban areas. Delayed spread occurred via river networks to more isolated areas in the rural interior. Understanding the patterns and timings of arboviral outbreak spread may allow targeted vector control measures at key transport hubs or in large transport vehicles.
Methods: A multifarious network of Aedes aegypti is addressed keeping the viewpoint of a complex system and modelled as a network. The dengue network has been transformed into a one-mode network from a two-mode network by utilizing projection methods. Furthermore, three network features have been analyzed, the power-law, clustering coefficient, and network visualization. In addition, five methods have been applied to calculate the global clustering coefficient.
Results: It has been observed that dengue epidemic follows a power-law, with the value of its exponent γ = -2.1. The value of the clustering coefficient is high for dengue cases, as weight of links. The minimum method showed the highest value among the methods used to calculate the coefficient. Network visualization showed the main areas. Moreover, the dengue situation did not remain the same throughout the observed period.
Conclusions: The results showed that the network topology exhibits the features of a scale-free network instead of a random network. Focal hubs are highlighted and the critical period is found. Outcomes are important for the researchers, health officials, and policy makers who deal with arbovirus epidemic diseases. Zika virus and Chikungunya virus can also be modelled and analyzed in this manner.
Methods: Patients were diagnosed with CHIK fever by a combination of virus isolation, viral RNA amplification, IgM antibody-, IgG antibody-, and/or neutralizing antibody detection. The whole-genome sequences of the CHIKV isolates were determined by next-generation sequencing.
Results: Prior to 2014, the source countries of the imported CHIK fever cases were limited to South and Southeast Asian countries. After 2014, when outbreaks occurred in the Pacific and Caribbean Islands and Latin American countries, there was an increase in the number of imported cases from these regions. A phylogenetic analysis of 14 isolates revealed that four isolates recovered from three patients who returned from Sri Lanka, Malaysia and Angola, belonged to the East/Central/South African genotype, while 10 isolates from 10 patients who returned from Indonesia, the Philippines, Tonga, the Commonwealth of Dominica, Colombia and Cuba, belonged to the Asian genotype.
Conclusion: Through the phylogenetic analysis of the isolates, we could predict the situations of the CHIK fever epidemics in Indonesia, Angola and Cuba. Although Japan has not yet experienced an autochthonous outbreak of CHIK fever, the possibility of the future introduction of CHIKV through an imported case and subsequent local transmission should be considered, especially during the mosquito-active season. The monitoring and reporting of imported cases will be useful to understand the situation of the global epidemic, to increase awareness of and facilitate the diagnosis of CHIK fever, and to identify a future CHIK fever outbreak in Japan.