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Research article
Ramesh C. Dhiman
National Institute of Malaria Research
Corresponding Author
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Background: Dengue is rapidly expanding climate-sensitive mosquito-borne disease worldwide. Outbreaks of dengue occur in various parts of India as well but there is no tool to provide early warning. The current study was, therefore, undertaken to find out the link between El Niño, precipitation, and dengue cases, which could help in early preparedness for control of dengue.
Methods: Data on Oceanic Niño Index (ONI) was extracted from CPC-IRI (USA) while the data on monthly rainfall was procured from India Meteorological Department. Data on annual dengue cases was taken from the website of National Vector Borne Disease Control Programme (NVBDCP). Correlation analysis was used to analyse the relationship between seasonal positive ONI, rainfall index and dengue case index based on past 20 years’ state-level data. The dengue case index representing ‘relative deviation from mean’ was correlated to the three months average ONI. The computed r values of dengue case index and positive ONI were further interpreted using generated spatial correlation map. The short-term (1 year) prediction of dengue probability map has been prepared based on phase-wise (El Niño, La Niña, and Neutral) 20 years averaged ONI.
Results: A high correlation between positive ONI and dengue incidence was found, particularly in the states of Arunachal Pradesh, Chhattisgarh, Haryana, Uttarakhand, Andaman and Nicobar Islands, Delhi, Daman and Diu. The states like Assam, Himachal Pradesh, Meghalaya, Manipur, Mizoram, Jammu & Kashmir, Uttar Pradesh, Orissa, and Andhra Pradesh shown negative correlation between summer El Niño and dengue incidence. Two –three month lag was found between monthly ‘rainfall index’ and dengue cases at local-scale analysis.
Conclusion: The generated map signifies the spatial correlation between positive ONI and dengue case index, indicating positive correlation in the central part, while negative correlation in some coastal, northern, and north-eastern part of India. The findings offer a tool for early preparedness for undertaking intervention measures against dengue by the national programme at state level. For further improvement of results, study at micro-scale (district) for finding month-wise association with Indian Ocean Dipole and local weather variables is desired for better explanation of dengue outbreaks in the states with ‘no association’.
Keywords
ENSO; Dengue case index; Early warning; Indian Ocean Dipole; Monsoon; post Monsoon.
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View the published article at BMC Public Health.
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On 24 Sep, 2020
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Submission checks complete
On 16 Sep, 2020
Editorial decision: Minor revision
On 15 Sep, 2020
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Review #1 received
Received 14 Aug, 2020
Reviewers invited
Invitations sent on 20 Jul, 2020
Reviewer #1 agreed
On 20 Jul, 2020
Editor assigned
On 19 Jul, 2020
Submission checks complete
On 18 Jul, 2020
Editor invited
On 18 Jul, 2020
No comments provided
Editorial decision: Major revision
On 03 Jun, 2020
Review #3 received
Received 25 May, 2020
Review #2 received
Received 25 May, 2020
Reviewer #3 agreed
On 30 Apr, 2020
Reviewer #2 agreed
On 27 Apr, 2020
Review #1 received
Received 14 Mar, 2020
Reviewer #1 agreed
On 21 Feb, 2020
Reviewers invited
Invitations sent on 12 Feb, 2020
Editor assigned
On 06 Jan, 2020
Submission checks complete
On 05 Jan, 2020
Editor invited
On 05 Jan, 2020
First submitted
On 03 Jan, 2020
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See the published version of this preprint at BMC Public Health.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research article
Ramesh C. Dhiman
National Institute of Malaria Research
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at BMC Public Health.
Version 4
Posted 24 Sep, 2020
No community comments so far
Submission checks complete
On 24 Sep, 2020
Editorial decision: Accept
On 24 Sep, 2020
No comments provided
Submission checks complete
On 16 Sep, 2020
Editorial decision: Minor revision
On 15 Sep, 2020
No comments provided
Review #1 received
Received 14 Aug, 2020
Reviewers invited
Invitations sent on 20 Jul, 2020
Reviewer #1 agreed
On 20 Jul, 2020
Editor assigned
On 19 Jul, 2020
Submission checks complete
On 18 Jul, 2020
Editor invited
On 18 Jul, 2020
No comments provided
Editorial decision: Major revision
On 03 Jun, 2020
Review #3 received
Received 25 May, 2020
Review #2 received
Received 25 May, 2020
Reviewer #3 agreed
On 30 Apr, 2020
Reviewer #2 agreed
On 27 Apr, 2020
Review #1 received
Received 14 Mar, 2020
Reviewer #1 agreed
On 21 Feb, 2020
Reviewers invited
Invitations sent on 12 Feb, 2020
Editor assigned
On 06 Jan, 2020
Submission checks complete
On 05 Jan, 2020
Editor invited
On 05 Jan, 2020
First submitted
On 03 Jan, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at BMC Public Health.
Background: Dengue is rapidly expanding climate-sensitive mosquito-borne disease worldwide. Outbreaks of dengue occur in various parts of India as well but there is no tool to provide early warning. The current study was, therefore, undertaken to find out the link between El Niño, precipitation, and dengue cases, which could help in early preparedness for control of dengue.
Methods: Data on Oceanic Niño Index (ONI) was extracted from CPC-IRI (USA) while the data on monthly rainfall was procured from India Meteorological Department. Data on annual dengue cases was taken from the website of National Vector Borne Disease Control Programme (NVBDCP). Correlation analysis was used to analyse the relationship between seasonal positive ONI, rainfall index and dengue case index based on past 20 years’ state-level data. The dengue case index representing ‘relative deviation from mean’ was correlated to the three months average ONI. The computed r values of dengue case index and positive ONI were further interpreted using generated spatial correlation map. The short-term (1 year) prediction of dengue probability map has been prepared based on phase-wise (El Niño, La Niña, and Neutral) 20 years averaged ONI.
Results: A high correlation between positive ONI and dengue incidence was found, particularly in the states of Arunachal Pradesh, Chhattisgarh, Haryana, Uttarakhand, Andaman and Nicobar Islands, Delhi, Daman and Diu. The states like Assam, Himachal Pradesh, Meghalaya, Manipur, Mizoram, Jammu & Kashmir, Uttar Pradesh, Orissa, and Andhra Pradesh shown negative correlation between summer El Niño and dengue incidence. Two –three month lag was found between monthly ‘rainfall index’ and dengue cases at local-scale analysis.
Conclusion: The generated map signifies the spatial correlation between positive ONI and dengue case index, indicating positive correlation in the central part, while negative correlation in some coastal, northern, and north-eastern part of India. The findings offer a tool for early preparedness for undertaking intervention measures against dengue by the national programme at state level. For further improvement of results, study at micro-scale (district) for finding month-wise association with Indian Ocean Dipole and local weather variables is desired for better explanation of dengue outbreaks in the states with ‘no association’.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
This is a list of supplementary files associated with this preprint. Click to download.
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