Countries at risk of importation of chikungunya virus cases from Southern Thailand: A modeling study

Epidemiologic Trends and Distributions of Imported Infectious Diseases Among Travelers to Japan Before and During the COVID-19 Pandemic, 2016 to 2021: A Descriptive Study

BACKGROUND

Little is known about the trends of imported infectious diseases among travelers to non-endemic countries during the novel coronavirus disease 2019 (COVID-19) pandemic. This article aimed to describe those among travelers to Japan.

METHODS

This is a descriptive study based on national surveillance data. Imported infectious disease cases were defined as those with a reported overseas source of infection among 15 diseases pre-selected based on the probability and impact of importation. The number of notified cases from April 2016 to March 2021 were described by disease and time of diagnosis. The relative ratio and absolute difference in case counts-both by number and per arrival-were calculated by disease comparing those from the pandemic period (April 2020-March 2021) to the pre-pandemic period (April 2016-March 2020).

RESULTS

A total of 3,524 imported infectious disease cases were diagnosed during the study period, including 3,439 cases before and 85 cases during the pandemic. The proportionate distribution of diseases changed but notification counts of all 15 diseases decreased during the pandemic. Accounting for arrivals, however, seven diseases showed a two-fold or greater increase, with a notable absolute increase per million arrivals for amebiasis (60.1; 95% confidence interval [CI], 41.5-78.7), malaria (21.7; 95% CI, 10.5-33.0), and typhoid fever (9.3; 95% CI, 1.9-16.8).

CONCLUSION

The epidemiology of imported infectious diseases changed during the pandemic. While the number of imported infectious disease cases decreased, the number of cases per arrivals increased considerably both in relative and absolute terms for several diseases of public health and clinical importance.

Virological, Serological and Clinical Analysis of Chikungunya Virus Infection in Thai Patients

From 2018 to 2020, the Chikungunya virus (CHIKV) outbreak re-emerged in Thailand with a record of more than 10,000 cases up until the end of 2020. Here, we studied acute CHIKV-infected patients who had presented to the Bangkok Hospital for Tropical Diseases from 2019 to 2020 by assessing the relationship between viral load, clinical features, and serological profile. The results from our study showed that viral load was significantly high in patients with fever, headache, and arthritis. We also determined the neutralizing antibody titer in response to the viral load in patients, and our data support the evidence that an effective neutralizing antibody response against the virus is important for control of the viral load. Moreover, the phylogenetic analysis revealed that the CHIKV strains we studied belonged to the East, Central, and Southern African (ECSA) genotype, of the Indian ocean lineage (IOL), and possessed E1-K211E and E1-I317V mutations. Thus, this study provides insight for a better understanding of CHIKV pathogenesis in acute infection, along with the genomic diversity of the current CHIKV strains circulating in Thailand.

Reducing dengue fever cases at the lowest budget: a constrained optimization approach applied to Thailand

Background

With the challenges that dengue fever (DF) presents to healthcare systems and societies, public health officials must determine where best to allocate scarce resources and restricted budgets. Constrained optimization (CO) helps to address some of the acknowledged limitations of conventional health economic analyses and has typically been used to identify the optimal allocation of resources across interventions subject to a variety of constraints.

Methods

A dynamic transmission model was developed to predict the number of dengue cases in Thailand at steady state. A CO was then applied to identify the optimal combination of interventions (release of Wolbachia-infected mosquitoes and paediatric vaccination) within the constraints of a fixed budget, set no higher than cost estimates of the current vector control programme, to minimize the number of dengue cases and disability-adjusted life years (DALYs) lost. Epidemiological, cost, and effectiveness data were informed by national data and the research literature. The time horizon was 10 years. Scenario analyses examined different disease management and intervention costs, budget constraints, vaccine efficacy, and optimization time horizon.

Results

Under base-case budget constraints, the optimal coverage of the two interventions to minimize dengue incidence was predicted to be nearly equal (Wolbachia 50%; paediatric vaccination 49%) with corresponding coverages under lower bound (Wolbachia 54%; paediatric vaccination 10%) and upper bound (Wolbachia 67%; paediatric vaccination 100%) budget ceilings. Scenario analyses indicated that the most impactful situations related to the costs of Wolbachia and paediatric vaccination with decreases/ increases in costs of interventions demonstrating a direct correlation with coverage (increases/ decreases) of the respective control strategies under examination.

Conclusions

Determining the best investment strategy for dengue control requires the identification of the optimal mix of interventions to implement in order to maximize public health outcomes, often under fixed budget constraints. A CO model was developed with the objective of minimizing dengue cases (and DALYs lost) over a 10-year time horizon, within the constraints of the estimated budgets for vector control in the absence of vaccination and Wolbachia. The model provides a tool for developing estimates of optimal coverage of combined dengue control strategies that minimize dengue burden at the lowest budget.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-10747-3.