Quantifying the localized relationship between vector containment activities and dengue incidence in a real-world setting: A spatial and time series modelling analysis based on geo-located data from Pakistan.

Increasing urbanization is having a profound effect on infectious disease risk, posing significant challenges for governments to allocate limited resources for their optimal control at a sub-city scale. With recent advances in data collection practices, empirical evidence about the efficacy of highl...

Full description

Bibliographic Details
Main Authors: Nabeel Abdur Rehman, Henrik Salje, Moritz U G Kraemer, Lakshminarayanan Subramanian, Umar Saif, Rumi Chunara
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-05-01
Series:PLoS Neglected Tropical Diseases
Online Access:https://doi.org/10.1371/journal.pntd.0008273
id doaj-9f7567437f574415904ff6be960f1878
record_format Article
spelling doaj-9f7567437f574415904ff6be960f18782021-03-03T07:56:33ZengPublic Library of Science (PLoS)PLoS Neglected Tropical Diseases1935-27271935-27352020-05-01145e000827310.1371/journal.pntd.0008273Quantifying the localized relationship between vector containment activities and dengue incidence in a real-world setting: A spatial and time series modelling analysis based on geo-located data from Pakistan.Nabeel Abdur RehmanHenrik SaljeMoritz U G KraemerLakshminarayanan SubramanianUmar SaifRumi ChunaraIncreasing urbanization is having a profound effect on infectious disease risk, posing significant challenges for governments to allocate limited resources for their optimal control at a sub-city scale. With recent advances in data collection practices, empirical evidence about the efficacy of highly localized containment and intervention activities, which can lead to optimal deployment of resources, is possible. However, there are several challenges in analyzing data from such real-world observational settings. Using data on 3.9 million instances of seven dengue vector containment activities collected between 2012 and 2017, here we develop and assess two frameworks for understanding how the generation of new dengue cases changes in space and time with respect to application of different types of containment activities. Accounting for the non-random deployment of each containment activity in relation to dengue cases and other types of containment activities, as well as deployment of activities in different epidemiological contexts, results from both frameworks reinforce existing knowledge about the efficacy of containment activities aimed at the adult phase of the mosquito lifecycle. Results show a 10% (95% CI: 1-19%) and 20% reduction (95% CI: 4-34%) reduction in probability of a case occurring in 50 meters and 30 days of cases which had Indoor Residual Spraying (IRS) and fogging performed in the immediate vicinity, respectively, compared to cases of similar epidemiological context and which had no containment in their vicinity. Simultaneously, limitations due to the real-world nature of activity deployment are used to guide recommendations for future deployment of resources during outbreaks as well as data collection practices. Conclusions from this study will enable more robust and comprehensive analyses of localized containment activities in resource-scarce urban settings and lead to improved allocation of resources of government in an outbreak setting.https://doi.org/10.1371/journal.pntd.0008273
collection DOAJ
language English
format Article
sources DOAJ
author Nabeel Abdur Rehman
Henrik Salje
Moritz U G Kraemer
Lakshminarayanan Subramanian
Umar Saif
Rumi Chunara
spellingShingle Nabeel Abdur Rehman
Henrik Salje
Moritz U G Kraemer
Lakshminarayanan Subramanian
Umar Saif
Rumi Chunara
Quantifying the localized relationship between vector containment activities and dengue incidence in a real-world setting: A spatial and time series modelling analysis based on geo-located data from Pakistan.
PLoS Neglected Tropical Diseases
author_facet Nabeel Abdur Rehman
Henrik Salje
Moritz U G Kraemer
Lakshminarayanan Subramanian
Umar Saif
Rumi Chunara
author_sort Nabeel Abdur Rehman
title Quantifying the localized relationship between vector containment activities and dengue incidence in a real-world setting: A spatial and time series modelling analysis based on geo-located data from Pakistan.
title_short Quantifying the localized relationship between vector containment activities and dengue incidence in a real-world setting: A spatial and time series modelling analysis based on geo-located data from Pakistan.
title_full Quantifying the localized relationship between vector containment activities and dengue incidence in a real-world setting: A spatial and time series modelling analysis based on geo-located data from Pakistan.
title_fullStr Quantifying the localized relationship between vector containment activities and dengue incidence in a real-world setting: A spatial and time series modelling analysis based on geo-located data from Pakistan.
title_full_unstemmed Quantifying the localized relationship between vector containment activities and dengue incidence in a real-world setting: A spatial and time series modelling analysis based on geo-located data from Pakistan.
title_sort quantifying the localized relationship between vector containment activities and dengue incidence in a real-world setting: a spatial and time series modelling analysis based on geo-located data from pakistan.
publisher Public Library of Science (PLoS)
series PLoS Neglected Tropical Diseases
issn 1935-2727
1935-2735
publishDate 2020-05-01
description Increasing urbanization is having a profound effect on infectious disease risk, posing significant challenges for governments to allocate limited resources for their optimal control at a sub-city scale. With recent advances in data collection practices, empirical evidence about the efficacy of highly localized containment and intervention activities, which can lead to optimal deployment of resources, is possible. However, there are several challenges in analyzing data from such real-world observational settings. Using data on 3.9 million instances of seven dengue vector containment activities collected between 2012 and 2017, here we develop and assess two frameworks for understanding how the generation of new dengue cases changes in space and time with respect to application of different types of containment activities. Accounting for the non-random deployment of each containment activity in relation to dengue cases and other types of containment activities, as well as deployment of activities in different epidemiological contexts, results from both frameworks reinforce existing knowledge about the efficacy of containment activities aimed at the adult phase of the mosquito lifecycle. Results show a 10% (95% CI: 1-19%) and 20% reduction (95% CI: 4-34%) reduction in probability of a case occurring in 50 meters and 30 days of cases which had Indoor Residual Spraying (IRS) and fogging performed in the immediate vicinity, respectively, compared to cases of similar epidemiological context and which had no containment in their vicinity. Simultaneously, limitations due to the real-world nature of activity deployment are used to guide recommendations for future deployment of resources during outbreaks as well as data collection practices. Conclusions from this study will enable more robust and comprehensive analyses of localized containment activities in resource-scarce urban settings and lead to improved allocation of resources of government in an outbreak setting.
url https://doi.org/10.1371/journal.pntd.0008273
work_keys_str_mv AT nabeelabdurrehman quantifyingthelocalizedrelationshipbetweenvectorcontainmentactivitiesanddengueincidenceinarealworldsettingaspatialandtimeseriesmodellinganalysisbasedongeolocateddatafrompakistan
AT henriksalje quantifyingthelocalizedrelationshipbetweenvectorcontainmentactivitiesanddengueincidenceinarealworldsettingaspatialandtimeseriesmodellinganalysisbasedongeolocateddatafrompakistan
AT moritzugkraemer quantifyingthelocalizedrelationshipbetweenvectorcontainmentactivitiesanddengueincidenceinarealworldsettingaspatialandtimeseriesmodellinganalysisbasedongeolocateddatafrompakistan
AT lakshminarayanansubramanian quantifyingthelocalizedrelationshipbetweenvectorcontainmentactivitiesanddengueincidenceinarealworldsettingaspatialandtimeseriesmodellinganalysisbasedongeolocateddatafrompakistan
AT umarsaif quantifyingthelocalizedrelationshipbetweenvectorcontainmentactivitiesanddengueincidenceinarealworldsettingaspatialandtimeseriesmodellinganalysisbasedongeolocateddatafrompakistan
AT rumichunara quantifyingthelocalizedrelationshipbetweenvectorcontainmentactivitiesanddengueincidenceinarealworldsettingaspatialandtimeseriesmodellinganalysisbasedongeolocateddatafrompakistan
_version_ 1714827036944498688