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Epidemiology and costs of dengue in Thailand: A systematic literature review [1]

['Usa Thisyakorn', 'Tropical Medicine Cluster', 'Chulalongkorn University', 'Bangkok', 'Surasak Saokaew', 'Center Of Health Outcomes Research', 'Therapeutic Safety', 'Cohorts', 'School Of Pharmaceutical Sciences', 'University Of Phayao']

Date: 2023-05 

Abstract Background Dengue is the fastest-spreading vector-borne viral disease worldwide. In Thailand, dengue is endemic and is associated with a high socioeconomic burden. A systematic literature review was conducted to assess and describe the epidemiological and economic burden of dengue in Thailand. Methods Epidemiological and economic studies published in English and Thai between 2011–2019 and 2009–2019, respectively, were searched in MEDLINE, Embase, and Evidence-Based Medicines reviews databases. Reports published by the National Ministry of Public Health (MoPH) and other grey literature sources were also reviewed. Identified studies were screened according to predefined inclusion and exclusion criteria. Extracted data were descriptively summarised and reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results A total of 155 publications were included in the review (39 journal articles and 116 grey literature). Overall, dengue incidence varied yearly, with the highest rates per 100,000 population in 2013 (dengue fever (DF) 136.6, dengue haemorrhagic fever (DHF) 100.9, dengue shock syndrome (DSS) 3.58) and 2015 (DF 133.1, DHF 87.4, DSS 2.14). Peak incidence coincided with the monsoon season, and annual mortality was highest for DSS, particularly in the age group 15–24-year-olds. The highest dengue incidence rates were reported in children (10–14-year-olds) and young adults (15-24-year-olds), irrespective of dengue case definition. Economic and societal burdens are extensive, with the average cost per case ranging from USD 41 to USD 261, total cost per year estimated at USD 440.3 million, and an average of 7.6 workdays lost for DHF and 6.6 days for DF. Conclusions The epidemiological, economic, and societal burden of dengue in Thailand is high and underreported due to gaps in national surveillance data. The use of expansion factors (EFs) is recommended to understand the true incidence of dengue and cost-benefit of control measures. Furthermore, as dengue is often self-managed and underreported, lost school and workdays result in substantial underestimation of the true economic and societal burden of dengue. The implementation of integrated strategies, including vaccination, is critical to reduce the disease burden and may help alleviate health disparities and equity challenges posed by dengue.

Author summary Dengue is a vector-borne viral disease affecting over 100 million people globally. In Thailand, dengue is endemic, but the true estimation of the disease burden is underreported. A systematic literature search for epidemiological (2011–2019) and economic (2009–2019) studies was conducted to analyse the disease incidence, seroprevalence, serotype distribution, mortality, expansion factor, and direct and indirect costs at a country and regional level. Peak dengue incidence was highest in 2013 and 2015 and overlapped with the annual monsoon season. Children and young adults were the most affected population, with the highest case fatality rates found in young adults aged 15–24 years with dengue shock syndrome (DSS). Limited evidence indicates a high economic and societal impact of dengue. These estimates place dengue as a significant public health concern in Thailand and emphasise the need for introducing an integrated disease management programme including vaccination strategies.

Citation: Thisyakorn U, Saokaew S, Gallagher E, Kastner R, Sruamsiri R, Oliver L, et al. (2022) Epidemiology and costs of dengue in Thailand: A systematic literature review. PLoS Negl Trop Dis 16(12): e0010966. https://doi.org/10.1371/journal.pntd.0010966 Editor: Hannah E. Clapham, National University Singapore Saw Swee Hock School of Public Health, SINGAPORE Received: May 10, 2022; Accepted: November 19, 2022; Published: December 19, 2022 Copyright: © 2022 Thisyakorn et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: All relevant data are within the manuscript and its Supporting Information files. Funding: This work was funded by Takeda Pharmaceuticals International AG. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: EG is an employee of Takeda. RK is a full-time employee of Takeda and is a Takeda stock holder. RS is an employee of Takeda (Thailand) Ltd. LO is an employee of Adelphi Values PROVE (Adelphi Values received budgetary compensation from Takeda for conduct of the study). RH is an employee of Takeda and has stock ownership in Takeda. Drs. UT and SS have declared no competing interests exist.

Introduction Dengue is the fastest-spreading vector-borne viral disease affecting over 100 million individuals per year globally. Over 70% of the population at risk of the disease are in the Southeast Asia and Western Pacific Regions [1]. Dengue is recognised as a major public health problem in Thailand affecting people of all ages, with cases reported from all four regions: North, Central, Northeast, and South [1,2]. The epidemics in the country follow a cyclic pattern, with the number of reported cases ranging from 20,000 to 140,000 per year for the period 2000 to 2011 [3]. Temperature, rainfall, and humidity contribute to the transmission cycle of dengue resulting in seasonal peaks with high incidence during the rainy season [4,5]. Infection with a dengue virus (DENV) typically causes asymptomatic infection or mild to moderate febrile illness. Globally, a small proportion of patients (about 5%) develop severe dengue, which can be life-threatening [6]. In Thailand, an average of 0.016 deaths per 100,000 population was reported for the period between 2000 and 2011, with the highest case fatality rates among young children [3]. At the febrile stage, dengue can be misdiagnosed as other diseases, including Zika, chikungunya, and COVID-19, due to the overlapping symptoms encompassing fever; rash; eye, muscle, and joint pains; vomiting; and headache [7–10]. Dengue is a notifiable disease in Thailand [3]. A nationwide passive surveillance system subject to inherent limitations is used to record dengue cases, severity, and demographics of detected cases. Both active and sentinel surveillances are rarely performed [3,11]. The 1997 World Health Organization (WHO) dengue case definition, which classifies dengue into three categories: DF, DHF, and DSS is extensively used in Thailand [3,12]. DF, a mild form of dengue often presents undifferentiated febrile disease that can lead to fatal DHF and DSS if not appropriately treated [13,14]. All cases are reported within 24 hours at the district level and are further aggregated at the provincial level and by the Bureau of Epidemiology [3]. In 2019, WHO designated dengue as one of the top ten threats to public health and the disease is associated with significant societal and economic burdens [15]. The true cost of the disease is likely underestimated due to underreporting and misdiagnosis of cases and dengue-related deaths owing to the wide spectrum of clinical presentations, and reliance on passive surveillance systems [16,17]. In 2013, the economic burden of dengue in Thailand was estimated at USD 424 million annually, and the total unit cost per case in 2010 was estimated at USD 793.6 [17,18]. Limited access to healthcare facilities across different populations and socioeconomic status further contributes to the underestimation of the disease burden. Given the high burden of dengue, understanding the epidemiological and cost trends in Thailand is essential for the allocation of health resources and the implementation of effective control and preventive strategies. A systematic literature review was conducted to assess and describe published data on the epidemiological and economic burden of dengue in Thailand and to update a previous literature review [3].

Methods The review was performed according to the Cochrane Handbook for Systematic Reviews guidelines [19] and the results are reported according to the PRISMA guidelines [20,21]. Data sources and search strategy To identify articles on the epidemiology and costs of dengue in Thailand, MEDLINE, Embase, and Evidence-Based Medicine reviews databases (Cochrane Database of Systematic Reviews, Cochrane Clinical Answers, Database of Abstracts of Reviews of Effects, and Health Technology Assessment) were searched via the OVID platform on 10 September 2019. Separate searches were conducted for epidemiological and cost burdens and restricted to articles published in English and Thai languages. The publication year was limited to 2011–2019 for the epidemiology burden, as a systematic literature review had already been conducted from 2000–2011 [3]. However, studies reporting data prior to 2011 and not captured in the previous systematic literature review were included in this review. For cost studies, the publication year was restricted to 2009–2019 (S1 Table). To identify additional articles, reference lists and grey literature sources including international and national surveillance databases and major academic websites were searched (S2 Table). Study selection Articles retrieved from the literature searches were deduplicated and thereafter screened against predefined eligibility criteria following a two-stage screening process. First, titles/abstracts were screened, and second, full texts were screened. At both stages, screening was done independently by two reviewers, and discrepancies were solved by a third reviewer. Studies were included in the review if they reported on the incidence, seroprevalence, serotype distribution, hospitalisation, mortality, EFs, or direct and indirect costs of dengue in Thailand (S3 Table). Study design criteria were not applied to grey literature because methods and sources for data collection/analysis are not clearly or often reported for this publication type. For studies with multiple publications, the source with the most recent or complete dataset was included. Data extraction and synthesis Relevant data were collected from each included publication onto a structured data extraction form. Data were extracted by one reviewer and cross-checked by a second reviewer. Any discrepancies were resolved by a third reviewer. Extracted data were descriptively synthesised. Data from national and regional surveillance sources were prioritised and supplemented with those from peer-reviewed publications where needed. For this reason, quality assessment was not performed because most of the included publications were from surveillance sources, and such assessment will not influence the data synthesis or certainty of the quality of evidence. No meta-analyses were conducted due to heterogeneity in the reported data. Costs were converted to 2019 USD using Thai consumer price index (CPI) [22].

Discussion The review describes the recent trends in the epidemiology and costs of dengue in Thailand. Overall, the annual incidence of dengue varied from 35.7 to 136.6 per 100,000 population for DF, from 26.7 to 100.9 per 100,000 population for DHF, and from 0.86 to 3.58 per 100,000 population for DSS, but the data were relatively stable throughout the review period except in the epidemic year of 2013 and 2015, which had the highest incidence [12,34]. The trends are similar to a previous review for Thailand that reported an average annual dengue incidence of 115 cases per 100,000 population for the period 2000–2011 [3]. From a regional perspective, the incidence of dengue varied year to year as observed at the national level (12). Across the review period, dengue cases were consistently high in the Central region as shown previously by Limkittikul et al., [3]. Overall, data from this study and previous studies depict a stable trend for national and regional incidence for the period 2000–2018 [3,12]. Nonetheless, the disease burden data should be interpreted cautiously, as national surveillance data represent reported cases and are not adjusted for underreporting. The seasonal impact of dengue was most evident during the rainy season, with most cases occurring from mid-May to mid-October each year [4,12,13,26,31,34]. This coincides with the monsoon season. The seasonal hikes together with the high burden of dengue in Thailand could overwhelm the healthcare systems and adversely impact the management and outcomes of other diseases [57]. Although the incidence of DHF and DSS was stable, the number of deaths in both disease groups increased throughout the review period, except in 2014 and 2016/2017 when it declined. The annual CFRs for the period ranged from 0.03%–0.1% for DHF and 3.35%–8.13% for DSS and surprisingly, 2014, which recorded the lowest number of deaths, also reported the second highest CFR for DSS during the review period. Throughout the period, the highest numbers of deaths were reported in the 15–24-year-olds followed by the 10–14-year-olds. In the literature review from Limkittikul et al., no deaths were recorded for DF between 2003 and 2011 [3]. However, in this review, deaths were reported in 2013 and consistently between 2015–2018. The mortality data should be carefully interpreted considering underreporting or misreporting of dengue-related deaths. From a national perspective, the age groups most impacted by dengue during the review period were the 10–14-year-olds (197.7 to 806.9 per 100,0000 population), the 5–9-year-olds (159.8 to 530.1 per 100,000), and the 15–24-year-olds (112.3 to 470.3 per 100,000 population), implying that in Thailand, dengue is primarily a disease of children and young adults as previously reported by Limkittikul et al. for the period 2000–2011 [3]. Hospitalisations due to dengue were high, ranging from 61.9%–65.7% at the national level. Higher rates, which varied by case definition and diagnostic status were observed at the regional level [12,17,23,25,29]. The majority of hospitalised cases were school children aged 6–18 years [23], and the rate was expectedly higher for DHF than for DF [12,23]. It is well documented that the four DENV serotypes co-circulate in Thailand [4, 58]. At the provincial level, DENV1 and DENV2 were mostly isolated [29,31,43,46,49,50,52,59, 60], with the DENV2 known to cause severe disease. The MoPH did not report national and regional serotype distributions. Data from publications were challenging to summarise due to variation in the predominant circulating serotype at the province/district level, and the distributions were not reported yearly [28,29,33,39,44,46,49,50,52,59,60]. The paucity of information highlights the need to continuously monitor the shift in serotype dominance, as it may help to forecast future major outbreaks [61]. National and regional seroprevalence data were not reported by the MoH. However, publications based on specific provinces and districts in Thailand showed diverse high seroprevalence rates, with one study conducted in Ayutthaya, Lop Buri, Narathiwat, and Trang, reporting seropositivity as high as 79.2% [41]. High rates of up to 84% were reported in the age groups between 2 and 19 years old, further highlighting the burden of dengue in children in Thailand [25,29,39,42]. Secondary dengue infections were more prevalent than primary infections, with studies from Yoon et al. (81.8%–97.4% vs. 0%–18.2%) and Buddhari et al. (85.9% vs. 2.8%) indicating high endemicity [33,45]. Dengue was also shown to impose a significant economic burden on the healthcare systems, households, and society, but the true burden may be underestimated due to underreporting and misreporting inherent in passive surveillance systems. Given that dengue is often self-managed by patients and that an outpatient visit or hospitalisation is the primary point of recording symptomatic dengue cases, the official reported cases represent only a fraction of the true burden of dengue. Estimation of the true burden is further skewed by regional and socioeconomic disparities and a lack of continuous reporting. Several studies identified in this systematic review highlight substantial underreporting of dengue cases in the national surveillance system, thus emphasising the need to adjust reported cases using EFs based on different settings and contexts to account for underreporting. In Nealon et al., substantial underreporting of symptomatic dengue cases was observed from passive surveillance systems in Thailand, resulting in the use of EFs of 8.6 to 12, depending on the case definitions. Similarly, Wichmann et al. highlighted the under-recognition of the burden of dengue by the passive surveillance systems in Thailand, with total symptomatic dengue cases 8.7-fold higher and inpatient cases 2.6-fold higher than recognised [14,27]. A previous economic systematic analysis estimated an EF of 8.5 for total dengue episodes in Thailand for the period 2001–2010 [62]. The paucity of national-level economic studies limits the estimation of true dengue economic burden in Thailand. Direct medical and non-medical costs may vary across the country. Societal and productivity costs are further challenged by the parameters included in the economic evaluations. Among the five studies identified in this review, three regional studies analysed productivity costs by considering data on school absenteeism, lost days at work, and days lost by either the patient or the caregiver during the illness [32,55,56]. Most of the studies only considered absenteeism from paid work and did not consider economic losses associated with lost unpaid work and costs incurred by informal caregivers. Altogether, economic burden is likely underestimated [63]. The strength of this review lies in the comprehensive evaluation of both the epidemiology and costs of dengue in Thailand over the past decade. However, several limitations exist. First, the literature search is liable to publication bias because publicly available studies/data were primarily identified. Second, incidence and mortality data were mostly obtained from grey literature sources and where possible, complemented with data from peer-reviewed studies. Further, the restriction to specific provinces or districts by most of the studies, as well as varying case definitions and dates of data collection hampered adequate comparison. Third, no publications reported seroprevalence data between 2017 and 2019; likewise, for serotype distribution, no data was available from 2015 to 2019. Fourth, in the cost analysis, only five studies were identified, and none stratified results by region and healthcare sector (private or public). Furthermore, variation in costs was observed due to the heterogeneity in methodological choices, which directly affects the comparison between the studies. Besides reporting on loss of working days, the broader macroeconomic impact of dengue has been overlooked. No studies included in the SLR analysed the impact of dengue on foreign direct investment or the income lost due to decreased tourism during seasonal dengue peaks and epidemics [32,55,56]. The true extent of direct and indirect costs incurred by lower socioeconomic sections poses a profound equity challenge [64]. Dengue epidemics are unpredictable and have been noticed in previously unaffected areas, with the spread of the dengue vector due to global climate changes, ineffective vector control methods, inconsistent surveillance, and travel [65,66]. Dengue vaccines could potentially reduce epidemiological and economic burden of dengue in Thailand [67]. Therefore, there is a need to evaluate effective dengue vaccination strategies and their cost-effectiveness to complement other preventive measures [68].

Conclusion Limited evidence is available for an accurate estimation of the dengue incidence and economic burden in Thailand. The overall burden of dengue in Thailand is high, with incidence rates varying year to year and national epidemics occurring every 2–4 years. Regardless of case definition, children are most affected, particularly the 5–14-year-old age group. Peak incidence corresponds with increased rainfall, and the impacts on terms of hospitalisations, deaths, and cost increase with disease severity. Economic and societal effects are substantial but underestimated due to underreporting and misreporting of cases. Therefore, it is essential to use EFs to adjust for underreporting so that the most effective public health interventions can be developed and implemented. Instead of limiting active surveillance to outbreak periods and settings only, continuous monitoring of dengue cases and serotypes is suggested to prevent, predict, and control future outbreaks. In view of the high cost and limited efficiency of vector control measures, further emphasis should be placed on evaluating vaccination strategies in integrated dengue management programmes to benefit broader population groups and alleviate socioeconomic disparities.

Acknowledgments The authors thank Egbe Ubamadu and Neha Agarwal (P95 Epidemiology and Pharmacovigilance, Leuven, Belgium) for updating the systematic literature review and providing medical writing support. The authors would also like to thank Ana Goios (P95 Epidemiology and Pharmacovigilance, Leuven, Belgium) for editing the manuscript draft and figures.

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