The Climate Risk Hiding in Your Access Data

This week, Northeast India is underwater. The Cabinet met to review flood damage across several states there while, six hundred kilometres west, central India is still waiting out a monsoon that arrived a day late and has been sulking ever since. The national rainfall deficit only narrowed from 30% to 14% in the last ten days. Same monsoon. Same year. Two opposite climate events, unfolding at once, inside the same country's health access numbers right now. Almost no dashboard tracking a CSR or patient access programme is built to tell them apart, which is the problem, because measuring climate's impact on health access starts exactly there.

Nine years inside pharma access and commercial work taught me one thing before anything else: a quarterly report never says "weather." It says "engagement fatigue," or "field team underperformance," or, more often, nothing, because the dip quietly disappears into an annual average nobody reopens. The report isn't lying. It's reading a column that was never built.

Why does a well-run access programme still show bad quarters?

Because the reporting template only asks two questions: did outreach happen, and did uptake happen. It never asks what happened in the district that week. A field team can execute a programme exactly as designed and still watch the numbers dip if the dip is weather, not delivery. The report then blames the field team, or the messaging, or "patient behaviour," the three excuses that absorb every unexplained number in this sector, and the actual driver goes untouched into next year's plan.

What does climate disruption actually look like inside operational data?

Ordinary, which is exactly the problem. Refill collection drops in the fortnight before a heatwave peaks, because people stop travelling in extreme heat before the news declares one. Outreach visit completion falls in flood-prone blocks during specific monsoon weeks, not the whole season evenly. Community health worker visit logs show gaps that line up with named weather events on a district calendar, not with anything in the worker's own performance history. Vendor delivery delays spike in windows that match flood advisories almost exactly, while the internal note says "logistics issue" and stops there.

Two decades ago, someone already proved this

In September 2008, floods hit rural Orissa and a team of researchers surveyed 29 primary health facilities to see how the system actually held up. Nineteen of them, 65.5%, reported that road access had been disrupted. Drug stock-outs ran six to ten days at the worst-hit sites, because central procurement places orders and makes payments at state level while supplies move at district level, so a single broken road severs the whole chain. Chronic disease management, hypertension, diabetes, stroke, was rated poor by 44.8% of the facilities. That paper has sat in the public record for close to two decades. Almost no CSR access programme built since has gone looking for it, because nobody thought to ask whether their own dip in September looked anything like it.

Heat writes its own signature on top of the monsoon's

Floods are the dramatic version. Heat is the quiet one, and it is currently the bigger economic story. India lost 247 billion labour hours to extreme heat in 2024 alone, worth an estimated USD 194 billion, roughly ₹18.5 lakh crore at July 2026 exchange rates (Lancet Countdown, 2025). Compared to the 1990s, the average Indian was exposed to 366 more hours of heat intense enough to cause physical stress. None of that shows up as a line item on a CSR programme's dashboard. It shows up as "adherence dropped in May" and gets filed next to the flood-season dip with the same shrug. I have written before about why the heat season is a healthcare operations problem, not a comfort one, and this is the data trail it leaves behind.

Is this a climate problem or an infrastructure problem?

Both, and arguing over which one matters more wastes the time you would spend fixing it. A heatwave hits a well-connected urban clinic and costs it a bad week. The same heatwave hits a rural block with one approach road and it costs a month, because the road and the cold chain fail together and the field team cannot travel at all. Climate stress and weak infrastructure compound each other rather than sitting as two separate line items you can address one at a time. A programme built without accounting for that compounding is designed for the district on a normal week, not the district on its worst one, which is precisely the week access actually breaks.

The report isn't lying. It's reading a column that was never built.

What does misdiagnosing this actually cost?

The WHO's global estimate is that roughly half of chronic disease patients do not take their medication as prescribed. A 2023 cross-sectional study in Mumbai found adherence at just 23.7% among a comparable patient group, well below the global baseline, and that number was measured without isolating a single heatwave or flood event as a variable. Layer climate disruption on top of an adherence problem that bad and you get a programme that keeps redirecting budget toward "poor uptake" fixes, more field staff and revised messaging, when the actual driver was a flood the programme never coded for. You end up optimising the wrong variable and calling the result a design failure when it was a measurement failure the whole time.

What does the BRSR clock have to do with any of this?

FY2026-27 is the year BRSR Core assurance extends from the top 500 to the top 1,000 listed companies, under SEBI's existing circular. A CSR health programme walking into that assurance with unexplained seasonal dips in its outcome data is not just leaving a gap in the report. It is handing an assurer a number it cannot defend, on a disclosure that is about to face real scrutiny for the first time. The programme might be well designed. The report will not be able to prove it.

How do you actually find this in your own numbers?

Pull the programme's visit, refill, and delivery data by week, not by quarter, because quarterly aggregation is exactly what hides this pattern. Overlay it against the district's heat action plan windows and any flood advisories issued that year. Check whether the "bad months" repeat on the same weeks across multiple years rather than appearing once. If a dip shows up every year in the same fortnight, in the same block, it isn't fatigue or a messaging problem. It's a weather signal wearing a performance label, and it has been sitting in a spreadsheet the whole time, waiting for someone to ask the right question of it.

The vocabulary for this gap already exists

This is what climate-access means: the specific point where a climate event severs the link between a patient and care they were already enrolled to receive. It is measurable, it is already sitting in most programmes' own data, and it is what a properly built diagnostic, the kind the CAST method is designed around, is meant to surface before an assurer finds it first.

Two states, same monsoon, same week, opposite weather. Your programme's data has been recording something like this every year it has run. Nobody built the column for it yet.

Abhijith Magal L

Founder, Syntropy Earth. Nine years across two global pharmaceutical multinationals in patient access and commercial roles, with health-equity work alongside the WHO-Foundation and UNICEF. He works on climate-access: where climate disruption breaks the link between patients and care.