A colossal challenge confronts us as a pandemic we understand little about sweeps across the globe. With 33 mutations of this virus, the use of data and technology to swiftly understand the changing landscape is more important than ever. Data communities across the globe are actively modelling, analysing and predicting the course forward. Similarly, in Pakistan, we are actively crunching the available information while at the same time seeking and collecting more. In light of the available data and information, projections and plans are put forth, iterated upon and revised almost daily with the hope that policymakers are swiftly consuming, iterating and planning accordingly.

Like the pandemic, while this global data-powered response and relief drive varies across the board, so does the local resource context that drives our response.

Here, I will attempt to contextualise the data from Pakistan that is publicly available and put forth the questions we must seek answers to.

According to the 2017 data from the WHO, Pakistan has 9.8 doctors and 6.68 nursing staff for every 10,000 people. There are more than 3,800 ventilators in the country, of which 2,200 are owned by the public sector. And another 2,500 ventilators were being added to the system. This comes as 46% of Pakistanis do not have access to water and soap at home.

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While the response and relief committees need to plan considering these bottlenecks, the Covid-19 tracking indicators also take on a new meaning once viewed from this resource-constrained lens.

Let’s take a look at the data coming in from the government. The positive cases are increasing — at a rate that is itself growing. However, this data is best understood in conjunction with the testing statistics coming in from across the country. Since the state started reporting testing statistics, the percentage of individuals testing positive has increased overall; however, this rate (positive cases/total tests) has been constant over the last three weeks.

The graph above plots the total positive cases to total tests ratio against date.

Once this rate is put in a global context, we see that there are huge variations across countries. The United Kingdom has a higher test:positive case ratio while South Korea, New Zealand and Taiwan, hailed for effectively controlling the pandemic amongst others, report a much lower statistic.

Let’s now look at the mortality rate calculated using the data of cumulative death over the total positive cases as reported by the government. Unfortunately, this statistic has steadily increased and continues to grow with Pakistan now at 2.1% mortality.

Let’s pause as we consume this data on the two most important indicators that characterise the pandemic. For any meaningful policy response, it will be critical to slice and dice this data set to reveal the nuances that the total numbers effectively mask.

The graph above plots the total deaths to total cases ratio against date.

Fortunately, we do have demographic breakup for these statistics. Fifty per cent of the positive Covid-19 patients lie in the age group of 20 to 49 years of age. However, this statistic is not mirrored as we slice the mortality numbers for Pakistan. A huge 83% of the deceased are from the age group 50 and above. Read this aloud and repeat.

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This statistic alone has critical policy implications. What segment of the population do we need to isolate as we smartly lockdown the country? What implication does this have for keeping mosques open for general public? Which sectors employ a greater percentage of this demographic?

As this breakdown leads to important policy questions, we then seek to ask more of the same. How does the pandemic spread vary within a province? What is the coverage of testing across districts? Are there any differences in the mortality rate across geographical divisions? How do urban areas compare to rural areas?

In Punjab, after Lahore, we see northern districts like Gujrat experience a rapid spread of the disease. Is this only because these cities saw a huge migrant population return? Or are there any other dynamics at play here? If the migrants returning can alone lead to such a rapid spread in one district, what other districts are at risk as we see more migrants return to their home country and native districts and villages? What is the mitigation policy?

As we ask these important questions, it is also important to discuss and streamline data reporting from tehsil and district headquarters. What is the hospitalisation and ventilator usage rate in each tehsil? As we debate the mortality numbers, ventilator usage and hospitalization are good indicators to track the spread and the intensity of the pandemic across the country. More importantly, are our hospitals in the tehsils and districts adequately staffed? Who is going to man the additional isolation facilities created in already understaffed localities? Do congested areas have access to more isolation wards?

This information is not only important for the state, but also for the organisations who have dived headlong into relief and response efforts. What areas are most in need of personal protective equipment, shields, and masks? Which areas need more doctors? These heat maps should not only be publicly available but also constantly updated as we respond to this pandemic together.

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As we understand the spread of the Covid-19 and plan for health contingencies accordingly, we are also amping up our testing facilities steadily. In South Asia, we are faring better than the rest of the region, but globally we still lag behind.

Given, that we have not opted for a complete lockdown, increasing testing all over the country becomes more important than other comparable regions. While the total testing numbers have steadily increased, the daily Covid-19 test rate is erratic. Is this only a reporting error or on some days more tests are conducted than on others? Again, how is this coverage spread district wise and what is the coverage for districts further away from the cluster of laboratories?

The answers to the questions asked will inform the public discourse, accelerate relief and response efforts and build confidence in the policies the state introduces in light of this sought-after data. Creating and updating heat maps in light of this data will only build trust and confidence in policies and the government apparatus, with its access to this national data updated daily at the National Command and Control Centre, can easily do it.

Clear data-driven communication will go a long way in buying compliance that is critical for the state. In addition, this will also enable community-driven monitoring that will only make the national response more formidable.

Header photo by Reuters