Understanding Climate-Related Educational Disruptions in Pakistan Through the Lens of Data, Inequality, and Policy

At a glance

Climate exposure is already part of the school-planning picture

This page brings together what the data can tell us about heat, extreme rainfall, and schools' ability to cope. It shows where the pattern is strongest and where a closer look may be useful.

What stands out

A few patterns are clear

The figures are a starting point for asking better local questions: which districts need a closer look, which hazard is driving the pattern, and where missing information is holding back a clear assessment.

Evidence behind the findings

Overview

Climate-related shocks can interrupt schooling, make attendance harder, and deepen existing inequalities in Pakistan. The 2022 floods alone disrupted schooling for an estimated 3.5 million children and pushed 1 million out of school entirely, with lower-income households bearing the greatest burden.

This project examines that problem by combining a scoping review, interviews with policymakers and data custodians, and analysis of climate, education, and socioeconomic data. Together, these strands map what is known, show where information is missing, and examine how climate shocks affect schools and learners differently.

At LUMS, CITY leads the geospatial and climate-exposure analysis, while the School of Education brings expertise in education policy and practice. The two teams work together to connect the data with the decisions it can inform.

Research questions

1. Where and when are schools in Punjab and Sindh exposed to extreme heat, extreme rainfall, and dry spells — and how many students, by school level and gender, are affected?
2. Do extreme climate events cause measurable enrolment disruption in Punjab government schools — how large, how persistent, and which school types are most affected?
3. Which districts and school categories face compounding climate exposure and educational vulnerability, and should be prioritised for climate-resilience investment?

Expected outputs

• A climate extremes and school exposure atlas for Punjab and Sindh, with ranked district and school lists.
• A comprehensive research report integrating the scoping review, interview findings, and secondary data analysis.
• A policy brief with actionable recommendations for climate-resilient education planning in Pakistan.
• A stakeholder policy roundtable, convened at LUMS, bringing together government, development partners, and academia to validate findings and discuss policy implications.

Research design

Approach

The project draws on three complementary methods, with stakeholder interviews iterating across all of them:

• Systematic scoping review — mapping academic, grey, and policy literature on climate-related educational disruption, following Arksey & O'Malley and PRISMA-ScR screening principles.
• Key informant interviews — semi-structured interviews with policymakers, researchers, development partners, and data custodians across Punjab, Sindh, Khyber Pakhtunkhwa, and Balochistan.
• Secondary data analysis — triangulating satellite-derived climate indices (ERA5, CHIRPS, Sentinel-1 SAR) with administrative education datasets (EMIS/SIS) for Punjab and Sindh, to detect climate-extreme episodes and map them against school exposure and enrolment.

Workstreams

How the school priorities are set

Each hazard is scored in two parts. First, the schools cumulative exposure is grouped as Low, Moderate, or High using the 33rd and 67th percentiles among schools exposed to that hazard. Second, the schools coping capacity is taken from the PMIU visit closest to one of its own hazard years. The two parts are then combined using the same table for heatwave and rainfall.

For heatwave, capacity combines electricity and drinking water. A dimension is Adequate when it is available, functional, and fully provided; it is Weak when it is unavailable or non-functional; otherwise it is Partial. The combined heat capacity is Adequate only when both dimensions are Adequate, Weak only when both are Weak, and Partial otherwise.

For extreme rainfall, capacity combines building condition, learning-space continuity, sanitation, and safe water. Learning space is Adequate at 90% or more of classrooms used for teaching, Partial at 70% to under 90%, and Weak below 70%. Sanitation uses the same 90% and 50% cut-offs for functional toilets. Structural condition and safe water use the recorded PMIU categories. Drainage is not scored because it is available only as sparse free text.

In the combined view, a school keeps the more severe of its two hazard priorities. A separate compounding flag is set only when both hazard priorities are 1 or 2.

Evidence atlas

Explore the evidence: Punjab School Climate-Exposure Atlas

Punjab School Climate Risk

Interactive view of the project data, with school names, locations, and priority categories.

Where the risk is Heat Extreme rainfall Find a school Method

This view brings the two hazards together. Each school is shown by whichever of its two hazard priorities is more severe.

52,196 (100%)

Schools tracked

18.7M

Students in exposed schools

10,279 (19.7%)

Urgent attention (P1–2)

103 (0.2%)

Both hazards at P1–2

Percentages are the share of 52,196 schools tracked across the two hazards.

Loading school locations…

Every tracked school, coloured by combined priority. Pan, zoom, and click a marker (or cluster) for details — the map updates with the sidebar filters and the legend below.

Map legend

Schools by combined priority

The first chart shows how many schools appear in each hazard record. The second shows where the 103 compounding Priority 1-2 schools are located.