District level weekly surveillance data on notifiable infectious diseases in Khyber Pakhtunkhwa Pakistan from 2023 to 2026

Abstract This article presents a structured, long-format panel dataset of district-week notifiable infectious disease case counts for Khyber Pakhtunkhwa (KP) province, Pakistan, covering 164 weekly epidemiological bulletins published between April 2023 and July 2026. The data were extracted from Table 4 of the National Institute of Health (NIH) Pakistan Integrated Disease Surveillance and Response (IDSR) weekly Public Health Bulletins, which reports district-level case counts for the most frequently reported notifiable conditions in KP each week. The dataset comprises 59,824 district-week-condition observations spanning 44 canonical district- and sub-division-level reporting units and 16 distinct notifiable conditions. Six conditions — acute diarrhoea (non-cholera), malaria, influenza-like illness, acute lower respiratory infection in children under five, bloody diarrhoea, and typhoid — are reported in all 164 bulletins. Ten further conditions appear only in a subset of weeks, because the non-core columns of the source table rotate according to that week’s case volume: from 2023 week 32 onward the table reports the highest-ranking conditions by provincial case total rather than a fixed set, producing 106 distinct column orderings across the corpus. The dataset documents this rotating-column structure explicitly, and is accompanied by a time-scoped district-name crosswalk resolving administrative-boundary changes over the study period — including one reporting label whose underlying geography is redefined mid-series — a week-by-week column-order log, a condition presence matrix, and machine-readable flags for identified source-side data-quality issues. No comparable structured, validated dataset derived from Pakistan’s national disease surveillance bulletins is currently available in the public domain.

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Publication Details

Journal
Research Square
Published
2026-11-01
DOI
https://doi.org/10.21203/rs.3.rs-11018824/v1
Primary Topic
Data-Driven Disease Surveillance
Type
preprint
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District level weekly surveillance data on notifiable infectious diseases in Khyber Pakhtunkhwa Pakistan from 2023 to 2026

Sania Ayub, Aamir Abbas, Khalid Nawab, Gulalai Khan et al.
2 links
Research Square
Data-Driven Disease Surveillance
preprint

District level weekly surveillance data on notifiable infectious diseases in Khyber Pakhtunkhwa Pakistan from 2023 to 2026

Sania Ayub, Aamir Abbas, Khalid Nawab, Gulalai Khan, Sara Nawab, Junaid Alam, Mohammad Ali
preprint en

Abstract

Abstract This article presents a structured, long-format panel dataset of district-week notifiable infectious disease case counts for Khyber Pakhtunkhwa (KP) province, Pakistan, covering 164 weekly epidemiological bulletins published between April 2023 and July 2026. The data were extracted from Table 4 of the National Institute of Health (NIH) Pakistan Integrated Disease Surveillance and Response (IDSR) weekly Public Health Bulletins, which reports district-level case counts for the most frequently reported notifiable conditions in KP each week. The dataset comprises 59,824 district-week-condition observations spanning 44 canonical district- and sub-division-level reporting units and 16 distinct notifiable conditions. Six conditions — acute diarrhoea (non-cholera), malaria, influenza-like illness, acute lower respiratory infection in children under five, bloody diarrhoea, and typhoid — are reported in all 164 bulletins. Ten further conditions appear only in a subset of weeks, because the non-core columns of the source table rotate according to that week’s case volume: from 2023 week 32 onward the table reports the highest-ranking conditions by provincial case total rather than a fixed set, producing 106 distinct column orderings across the corpus. The dataset documents this rotating-column structure explicitly, and is accompanied by a time-scoped district-name crosswalk resolving administrative-boundary changes over the study period — including one reporting label whose underlying geography is redefined mid-series — a week-by-week column-order log, a condition presence matrix, and machine-readable flags for identified source-side data-quality issues. No comparable structured, validated dataset derived from Pakistan’s national disease surveillance bulletins is currently available in the public domain.

Research Square
Pennsylvania State University (US), Khyber Medical College (PK), University of Swat (PK), Vital Pakistan Trust (PK)
Good health and well-being
Data-Driven Disease Surveillance
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