A Spatial Hierarchical Analysis of the Temporal Influences of the El Niño-Southern Oscillation and Weather on Dengue in Kalutara District, Sri Lanka

Liyanage, Prasad; Tissera, Hasitha; Sewe, Maquins; Quam, Mikkel; Amarasinghe, Ananda; Palihawadana, Paba; Wilder‐Smith, Annelies; Louis, Valéerie R.; Tozan, Yesim; Rocklöv, Joacim

doi:10.3390/ijerph13111087

Cited by 45 publications

(52 citation statements)

References 52 publications

(83 reference statements)

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“…Similar to Xiao et al [62], Liyanage et al [63] also reported ENSO dengue associations. They used the Oceanic Niño Index (ONI) to explore ENSO's impact on dengue incidence over 10 Medical Officer of Health divisions in the Kalutara district of Sri Lanka for the period 2009-2013.…”

Section: Denguesupporting

confidence: 62%

El Niño Southern Oscillation (ENSO) and Health: An Overview for Climate and Health Researchers

McGregor

Ebi

2018

Atmosphere

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Abstract:The El Niño Southern Oscillation (ENSO) is an important mode of climatic variability that exerts a discernible impact on ecosystems and society through alterations in climate patterns. For this reason, ENSO has attracted much interest in the climate and health science community, with many analysts investigating ENSO health links through considering the degree of dependency of the incidence of a range of climate diseases on the occurrence of El Niño events. Because of the mounting interest in the relationship between ENSO as a major mode of climatic variability and health, this paper presents an overview of the basic characteristics of the ENSO phenomenon and its climate impacts, discusses the use of ENSO indices in climate and health research, and outlines the present understanding of ENSO health associations. Also touched upon are ENSO-based seasonal health forecasting and the possible impacts of climate change on ENSO and the implications this holds for future assessments of ENSO health associations. The review concludes that there is still some way to go before a thorough understanding of the association between ENSO and health is achieved, with a need to move beyond analyses undertaken through a purely statistical lens, with due acknowledgement that ENSO is a complex non-canonical phenomenon, and that simple ENSO health associations should not be expected.

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Section: Denguesupporting

confidence: 62%

El Niño Southern Oscillation (ENSO) and Health: An Overview for Climate and Health Researchers

McGregor

Ebi

2018

Atmosphere

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“…Liyanage et al pointed that both rainfall and temperature are significantly associated with risk of dengue in the Kalutara district of Sri Lanka [24]. Also they described a strong relationship between the oceanic El Nino index to weather patterns and to dengue at a longer latency time.…”

Section: Fig 1 Map Of Sri Lanka (Eastern Province Has Been Colored)mentioning

confidence: 99%

“…Most of climate studies on dengue have been done in the central province and Western province of Sri Lanka [23,24,26], where the climate differs significantly from that of the Eastern province of Sri Lanka. Only few studies have been done on the relationship between climate and dengue incidences in Batticaloa [5] and those studies were limited to data which were collected from only Batticaloa district in the Eastern Province of Sri Lanka.…”

Section: Chakravarti Et Al Designed a Relationship Of Dengue Infectimentioning

confidence: 99%

Impact of Climatic Factors on Dengue Incidences in Eastern Province, Sri Lanka

Karunarathna

Sriranganesan

2020

IJTDH

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Introduction: Health sector is one of the most important sectors of any country. Many aspects such as diseases, health practices, and institutions are associated with health. Among different infectious diseases, dengue has become a major health issue for human in most tropical and subtropical regions. It is a viral disease originated and spread from mosquito and it is in several forms. Since, this seriously affects human life, taking necessary measures, including policies, rules, regulation and best practices to bring this menace into a minimum level, is essential. Such actions require proper background about the disease including factors that this disease depends on. Several factors may be associated with dengue fever and climatic variables take a greater place. Effect of these variables may vary from area to area. Aims: This study aimed to investigate the impact of climatic variables for progression of dengue disease in the Eastern Province of Sri Lanka, which is consisted of three districts: Batticaloa; Trincomalee and Ampara. Study Design: Number of dengue incidences and climatic variables such as rainfall, temperature, number of rainy days, day time humidity, night-time humidity, number of sunny days, and UV Index were obtained for each month in the period from 2009 to 2017 from Meteorology Department and statistical abstracts of Sri Lanka. Analysis was carried out by using the statistical techniques: correlation analysis; regression analysis; principle component analysis and a graphical technique, contour maps. Results: Only a few climatic factors affect dengue incidences in these three districts. However, no any regular pattern could be observed. Impact of each climatic factor varies from district to district. In Batticaloa district, a number of rainy days and day time humidity affect dengue incidences negatively and positively respectively meanwhile wind speed positively affects dengue incidences in Ampara district. No any climatic variables in Trincomalee district show a relationship with dengue incidences in the district. In general, moderate humidity creates a favourable situation for the spread of dengue disease irrespective of districts. Heavy rainfall does not show a relation with dengue incidences as people believe. Conclusion: It is difficult to investigate the impact of each climatic factor alone on dengue incidences because there are inter correlated. Number of dengue incidences may depend on many other variables such as population density, geographical location, health practices, personal health status, knowledge, policies of different institutes and organizations. It is essential to incorporate these sorts of variables also to have a proper understanding of the dengue disease and its spread.

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“…Weekly weather and dengue data, measured in 10 divisions in Kalutara, a district in Sri Lanka were retrieved and analysed [13]. Distributed lag non-linear time series analysis was used to estimate division-specific risks, and hierarchical models were fitted to estimate the overall relationships between el Niño conditions, weather and dengue across divisions.…”

Section: Specific Objectivesmentioning

confidence: 99%

Novel tools for the surveillance and control of dengue: findings by the DengueTools research consortium

Wilder‐Smith

Tissera

AbuBakar

et al. 2018

Global Health Action

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Background: Dengue fever persists as a major global disease burden, and may increase as a consequence of climate change. Along with other measures, research actions to improve diagnosis, surveillance, prevention, and predictive models are highly relevant. The European Commission funded the DengueTools consortium to lead a major initiative in these areas, and this review synthesises the outputs and findings of this work conducted from 2011 to 2016. Research areas: DengueTools organised its work into three research areas, namely [1] Early warning and surveillance systems; [2] Strategies to prevent dengue in children; and [3] Predictive models for the global spread of dengue.Research area 1 focused on case-studies undertaken in Sri Lanka, including developing laboratory-based sentinel surveillance, evaluating economic impact, identifying drivers of transmission intensity, evaluating outbreak prediction capacity and developing diagnostic capacity. Research area 2 addressed preventing dengue transmission in school children, with case-studies undertaken in Thailand. Insecticide-treated school uniforms represented an intriguing potential approach, with some encouraging results, but which were overshadowed by a lack of persistence of insecticide on the uniforms with repeated washing. Research area 3 evaluated potential global spread of dengue, particularly into dengue-naïve areas such as Europe. The role of international travel, changing boundaries of vectors, developing models of vectorial capacity under different climate change scenarios and strategies for vector control in outbreaks was all evaluated. Concluding remarks: DengueTools was able to make significant advances in methods for understanding and controlling dengue transmission in a range of settings. These will have implications for public health agendas to counteract dengue, including vaccination programmes. Outlook: Towards the end of the DengueTools project, Zika virus emerged as an unexpected epidemic in the central and southern America. Given the similarities between the dengue and Zika viruses, with vectors in common, some of the DengueTools thinking translated readily into the Zika situation.

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A Spatial Hierarchical Analysis of the Temporal Influences of the El Niño-Southern Oscillation and Weather on Dengue in Kalutara District, Sri Lanka

Cited by 45 publications

References 52 publications

El Niño Southern Oscillation (ENSO) and Health: An Overview for Climate and Health Researchers

El Niño Southern Oscillation (ENSO) and Health: An Overview for Climate and Health Researchers

Impact of Climatic Factors on Dengue Incidences in Eastern Province, Sri Lanka

Novel tools for the surveillance and control of dengue: findings by the DengueTools research consortium

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