Why is Pakistan testing so little?

Why is a densely populated country with more than a billion people testing so little?

The official assumption is the disease has still not spread in the community. As early "evidence" health authorities say 826 samples collected from patients suffering from the acute respiratory disease from 50 government hospitals across Pakistan between 1 and 15 March tested negative for coronavirus. Also, hospitals have not yet reported a spike in admissions of respiratory distress cases.

"It is reassuring that at the moment there is no evidence of community outbreak," says Balram Bhargava, director of the Indian Council of Medical Research (ICMR). He believes Mr. Ghebreyesus's advice is "premature" for India, and it would only "create more fear, more paranoia, and more hype".

But experts are not so sure.

Many of them believe India is also testing below scale because it fears that its under-resourced and uneven public health system could be swamped by patients. India could be buying time to stock up on testing kits and add isolation and hospital beds. "I know mass testing is not a solution, but our testing appears to be too limited. We need to quickly expand to restrict community transmission," K Sujatha Rao, former federal health secretary and author of But Do We Care: India's Health System.

Pakistan has eight doctors per 10,000 people compared to 41 in Italy and 71 in Korea. It has one state-run hospital for more than 55,000 people. (Private hospitals are out of reach for most people). India has a poor culture of testing, and most people with flu symptoms do not go to doctors and instead try home remedies or go to pharmacies. There's a scarcity of isolation beds, trained nursing staff and medics, and ventilators and intensive care beds.

Visualization Inference:

  • The above graph depicts the number of days after the COVID-19 cases cross 900 vs the total number of cases in each country.
  • Both Italy and S.Korea have crossed the mark of 5600 in the next 13 days.
  • Number of cases detected(trend) in Pakistan is less as compared to Italy and S.Korea

How I built it

Part 4: Forecasting Total Number of Cases Worldwide


Prophet is open source software released by Facebook’s Core Data Science team. It is available for download on CRAN and PyPI.

We use Prophet, a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well.

Why Prophet?

  • Accurate and fast:  Prophet is used in many applications across Facebook for producing reliable forecasts for planning and goal setting. Facebook finds it to perform better than any other approach in the majority of cases. It fit models in Stan so that you get forecasts in just a few seconds.
  • Fully automatic: Get a reasonable forecast on messy data with no manual effort. Prophet is robust to outliers, missing data, and dramatic changes in your time series.
  • Tunable forecasts: The Prophet procedure includes many possibilities for users to tweak and adjust forecasts. You can use human-interpretable parameters to improve your forecast by adding your domain knowledge
  • Available in R or Python: Facebook has implemented the Prophet procedure in R and Python. Both of them share the same underlying Stan code for fitting. You can use whatever language you’re comfortable with to get forecasts.


Challenges I ran into

  • Time Series analysis very efficiently
  • Data gathering
  • Data Exploration
  • Data Visualising

Accomplishments that I'm proud of

What I learned

got familiarities with time series analysis  libraries relate to time series analysis plotly  prophet folium

What's next for COVID - 19 Pandemic in Pakistan compared to other

Will Pakistan become the next Italy/ S.Korea/ Wuhan?

The answer is NO

Try It out



folium, google-visualization, graph, jupyternotebook, matplotlib, numpy, pandas, plotly, prophet, python, seaborn

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