Geospatial clustering and hot spot detection of malaria incidence in Bahawalpur district of Pakistan

Fatima, Mahvish; Butt, Ibtisam; Arshad, Sana

doi:10.1007/s10708-021-10535-x

Cited by 7 publications

(4 citation statements)

References 39 publications

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“…It has seen massive population growth in the last 30 years, leading to an increased risk of infectious diseases and epidemics (Arshad et al, 2022). Pakistan has experienced outbreaks of dengue (Khan et al, 2022), malaria (Fatima et al, 2022), cholera (Naveed et al, 2022), and other infectious diseases during this period (Zohra et al, 2021). The COVID-19 pandemic had a significant impact on public health, hospitals, and other sectors of the economy in Pakistan (Kanwar et al, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

Transforming Adversity Into Opportunity: Assessing User Satisfaction in Hospital Transformation in Lieu of a Pandemic Through the Multi-Corridor Expansion Model for Epidemic Management and Environmental Design Enhancement

Bhatti,

Ghufran,

Shah

2023

NJEDP

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The COVID-19 pandemic brought the world to a standstill, demonstrating the critical importance of preparedness and adaptation in the face of pandemics and epidemics. Pandemics and epidemics have been a persistent threat throughout human history, causing significant mortality and morbidity, as well as disrupting economies, societies, and politics. The COVID-19 pandemic, caused by the SARS-CoV-2 virus, had a profound impact on healthcare systems worldwide, leading to hospitals transforming into pandemic centers. This case study, conducted at Riphah International Hospital (RIH) in Islamabad, Pakistan, explores the transformation of an existing facility into a pandemic center, highlighting the challenges faced in managing the pandemic conditions and ensuring the safety of the public and medical teams. The study was based on an observational study and data collection from end users with respect to transformation satisfaction and issues faced. Spatial segregation, logistics, air flow control, managing infection control, etc were major challenges faced and managed. Stress was high for the end users who facilitated in medical teams. The study emphasizes the critical importance of preparedness and adaptation in the face of pandemics/epidemics, including the need for specialized training of medical personnel, dedicated COVID-19 units in hospitals, and a robust and resilient healthcare system that can manage future epidemics.

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Section: Literature Reviewmentioning

confidence: 99%

Transforming Adversity Into Opportunity: Assessing User Satisfaction in Hospital Transformation in Lieu of a Pandemic Through the Multi-Corridor Expansion Model for Epidemic Management and Environmental Design Enhancement

Bhatti,

Ghufran,

Shah

2023

NJEDP

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“…A Z-Score is an anomaly detection tool that is able to determine features where outliers do and do not exist in a time series (see e.g., Fatima et al, 2021;Rousseeuw & Hubert, 2018). In our analysis, zero-approaching Z-Score values were used to determine intense clustering of values that remained convergent over high values of the DM and the SED over the domain of Pakistan.…”

Section: Z-score For Hotspot Analysismentioning

confidence: 99%

On the emergence of a predicted climate change signal: When and where it could appear over Pakistan

Khan¹,

Wazir²,

Bokhari³

et al. 2023

EUR J SUSTAIN DEV RES

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Emergence of climate change signal attributed to change in mean temperature can bring serious implications to economic stability of developing countries like Pakistan. Likewise, unawareness of vulnerability in regions of a country can direct mitigation efforts towards unwanted areas instead of towards ones that are genuinely deprived of. To address these two issues for Pakistan, we adopted a compendium of five metrics by using climate model data of near surface mean monthly temperature from output of a general circulation model MRI-ESM2-0 of Meteorological Research Institute (MRI), simulated under historical (1850-2014) and projected (2015-2100) periods for five shared socioeconomic pathways (SSPs) described in the sixth assessment report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) originally published in the year 2021. To identify potential hotspot regions, we used four out of the five metrics i.e., change in mean (DM–vulnerability metric), standard Euclidean distance (SED–vulnerability metric), change in standard deviation (DSD–stability metric), and standard score (Z-Score–stability metric) statistics for regional bounds of Pakistan. To investigate emergence of climate change signal, we computed the fifth metric viz. signal to noise ratio (SNR–agility metric) from time series of the near surface mean monthly temperature and checked how rapidly the subject signal emerged out of variability in the studied data under different scenarios. On the estimation of vulnerability and stability, our results revealed that the Himalayan region of Pakistan (the northeast corner) repeatedly appeared to be the most qualified region to be acclaimed as a hotspot due to its reach to optimal echelons in the associated metrics of the DM (more than four degrees), the SED (up to one), the DSD (close to null) and the Z-Score (close to null) under all the studied SSP scenarios. On the estimation of agility, our results revealed that owing to allegedly sustainable scenarios (with low to medium challenges to mitigation), the SSP1, the SSP2, and the SSP4 delayed the evolution of climate change signal (between 2070 to 2100) by at least two decades as compared to allegedly perplexing (high challenges to mitigation) SSP3 and SSP5 scenarios that accelerated the appearance of the signal by crossing the SNR threshold fairly earlier (between 2040 to 2060) in the 21<sup>st</sup> century. With such knowledge at hand, this scientific contribution can advise policymakers and stakeholder agencies to exercise conversant decisions and to equip themselves with evidence to prioritize and target their resources in an informed way over Pakistan region.

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“…In summary, this method assess the malaria prevalence rates for each area with rates in surrounding areas at a fixed distance. In addition, the same method has been applied by (Fatima et al, 2021) to examine spatial clustering and outlier's detection of Covid-19 incidence in 2020.…”

Section: Spatial Clustering Of Malariamentioning

confidence: 99%

Malaria in Kenya during 2020: malaria indicator survey and suitability mapping for understanding spatial variations in prevalence and risk

Kioko,

Blanford

2023

AGILE GIScience Ser.

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Abstract. Despite the availability of effective interventions malaria continues to be a major public health issue in Kenya, where young children and pregnant women are particularly vulnerable. In this study we examined the spatial distribution of malaria incidence and how this relates to the environmental conditions required for malaria in 2020. The Kenya Malaria Indicator Survey (N=11,549) for 2020 was used with the Local Indicators of Spatial Autocorrelation (LISA) method to determine spatial clusters of malaria and assess their significance as well as interventions in use. Climate data was used with a Fuzzy Overlay method to create malaria risk maps. The findings suggest that malaria incidence is not evenly distributed across Kenya, with some regions having higher rates of transmission and others having lower rates. High-rate clusters of malaria and high-risk areas of malaria transmission could benefit from increased vector control measures.

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Geospatial clustering and hot spot detection of malaria incidence in Bahawalpur district of Pakistan

Cited by 7 publications

References 39 publications

Transforming Adversity Into Opportunity: Assessing User Satisfaction in Hospital Transformation in Lieu of a Pandemic Through the Multi-Corridor Expansion Model for Epidemic Management and Environmental Design Enhancement

Transforming Adversity Into Opportunity: Assessing User Satisfaction in Hospital Transformation in Lieu of a Pandemic Through the Multi-Corridor Expansion Model for Epidemic Management and Environmental Design Enhancement

On the emergence of a predicted climate change signal: When and where it could appear over Pakistan

Malaria in Kenya during 2020: malaria indicator survey and suitability mapping for understanding spatial variations in prevalence and risk

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