While COVID rages on globally and across India a more spirited debate ranges in my mind. Was there a way to anticipate and proactively move on infectious and non infectious conditions in India?
One thing that COVID has exposed is the gross unpreparedness of the Indian healthcare system to deal with pandemics. But it also exposed how little we knew about the situation on the ground. Data available is inadequate and most of the data especially from the villages and districts is not captured.
At the front line for the fight against disease and other illnesses is the Indian Primary Care system. This system is mostly run by ASHA (Accredited Social Health Activists) If something is coming our way, they are the first to know. And while they have been around since the recommendations of the Bhore Committee recommendations were given in 1943, it is easy to see how they are ill-prepared to deal with anything.
This is some data that I have been able to ascertain from public sources.
Number of ASHA Workers
Number of primary health centers
Average Salaries of ASHA Workers
Average costs incurred by ASHA WOrkers
So this is the on-ground scenario. These workers have to fill multiple forms for child care, maternal care among others, and then they have made 10-15 home visits per day. There are key reasons why ASHA workers are important.
They are local to an area, they understand the local customs and traditions
They have the trust of the community, communitites in rural India do not like to discuss their health with strangers
While are part timers, going from home to home makes them the best eyes and ears for the healthcare system
But given their situation and low pay, would it be interesting to see what we can do to help their situation. The government is spending close to INR 5000 Crore on the Ayushman Bharat Program. Next year the outlay is close to 10,000 Crore. But at a fraction of this cost, we can increase the pay for the ASHA workers and get much better coverage to prevent patients from getting hospitalized.
In the coming days, I would be focusing on how we can strengthen the primary care system and improve the overall effectiveness of the ASHA workers while providing them better remuneration for their tasks.
We did this video to talk about the challenges of the primary healthcare system. Below is the recording for the same.
As always we look forward to your comments and suggestions on the same.
Recently, Dr Devi Shetty, the founder of Narayana Hrudayalaya, authored an article in the Times of India Sunday Edition where he said that healthcare will become a poll issue in the future. Given the historically low percentage of budget allocated to public health in India, can Covid19 realistically push the government to prioritise this area?
An analysis of select 2014 election manifestos indicates that we may be woefully behind on the path to a more comprehensive health plan for citizens.
India spends about 1.2% of its GDP on health services and in 2018 this number went up to 1.4%. However, this is still significantly lower than the time and efforts allocated to areas like physical infrastructure development and jobs.
Women Led parties had more space dedicated to healthcare in their election manifestos (AIADMK – 6% and TMC – 5%). AAP follows closely with 4%, whereas national parties BJP and Indian National Congress (INC) dedicated around 2.3% and 2.1%, respectively. Interestingly, the AIADMK appears to have been implemented given that Tamilnadu leads on several health parameters, the TMC in West Bengal needs a stronger implementation policy to suitably action on its promise.
Most parties tend to pay little attention to preventive health. There is almost no mention of areas like nutrition in election manifestos and while the BJP manifesto does talk about Swachh Bharat, there is no mention of ways to tie that back to measuring health outcomes. The INC manifesto talks about malnutrition and mentions Anaemia and HIV but does not spell out anything concrete in terms of action plans to prevent or tackle the disease.
All election manifestos considered for analysis missed addressing non-communicable diseases and the measures to tackle them. Given the high incidence of non-communicable diseases such as diabetes and hypertension in India, this is a glaring miss.
Most of the focus on health in manifestos is on building hospitals – more beds and more clinics and so on. But there is no focus on the quality of care provided at these centres or the variety of ailments they can treat. One cannot provide hospitalisation and expect improvement in the state of health without tackling the underlying social and sanitation causes for the ailments.
Strangely, while the focus remains on building new facilities, there is no mention of improving existing primary health centres and community health centres that have suffered from decades of neglect. Even in Ayushman Bharat these have not been addressed. While the insurance part of Ayushman Bharat is doing well, the wellness program can be significantly improved.
There is no mention of disease surveillance in any manifesto. This is surprising considering most developing countries in the world have some semblance of proactive disease surveillance to curb the spread of disease and manage its citizens’ health.
In summary, even if all that has been promised in the election manifesto is delivered, it would not even make a dent in the state of health in the country.
Why is this so?
Historically India missed the boat in prioritising healthcare reforms recommended by the Bhore committee in 1946 (See box in the next page), particularly the delivery of health at the grass root levels through primary health centres (PHCs).
Further, religious beliefs that tie poor health to karma and a generally fatalistic outlook have ensured hospitals and external care providers are seen as the last resort for patients. Preventive healthcare was largely provided at home. In line with this, the government has not undertaken research connecting the health of its citizens to their productivity. For instance, a study in the UK found that those who smoked were twice as likely to take time off work. Another study found that workers with obesity (BMI over 30) annually took an average of three sick days more than those with normal weight (BMI less than 25), and those with severe obesity (BMI over 35) took six days more. In India, a large population and limited availability of jobs means employment remains a bigger issue than health for the government.
The relatively affordable cost of healthcare so far has also meant citizens have remained negligent about lifestyle diseases. Until recently health insurance wasn’t understood and perhaps without the tax exemption many citizens may not opt for it.
Until the time healthcare is viewed as a discretionary spend, political parties may see no value in contesting elections on the plank of better healthcare for citizens. Citizens themselves need to demand for better health from its government for parties to take the issue seriously. A possible reason why some of the Southern states have overall better health indicators is the relatively high proportion of senior citizen population that resides alone, without support from younger people who tend to live outside the state/ country. This changing demographic of voters may have prompted political parties in the region to place greater emphasis on public health and deliver results.
In addition states like Karnataka and Kerala have prospered from the investments from the princely states. Tamilnadu alone benefitted by keeping public health distinct from Health Services, this is one of the few states that implemented this recommendation from the Bhore Committee recommendations.
The following part manifestos were considered for the analysis – Bhartiya Janata Party (BJP), Indian National Congress (INC), All India Anna Dravida Munnetra Kazhagam (AIADMK), Trinamool Congress (TMC) and Aam Aadmi Party (AAP). The rationale was to consider national level parties and those led by women, as it is widely acknowledged that women tend to prioritise health. (We wanted to include the Bahujan Samaj Party (BSP) but we couldn’t find the manifesto in the public domain). AAP was considered in the analysis as it was a recently formed political party that emerged from a citizen movement demanding a corruption free India. All manifestos from 2014 were considered for the analysis.
The following parties have not been considered as their manifestos were unclear on the healthcare aspect – JDS Karnataka, Shiv Sena, Shiromani Akai Dal, and Biju Janata Dal. The communist parties are also missing from our analysis. We are planning a follow up report on the analysis of the 2019 manifestos and we plan to include more parties there.
Since our last article, new Covid19 cases have started showing a declining trend in the countries most affected by the virus. India, on the other hand, has started showing a disturbing trend. The ‘42 day theory’ has held true for all the countries under study (except S.Korea, an outlier). Will it hold true for India or will India also be an outlier to this theory?
With declining new cases, the recovery rates and the mortality rates start to come in play. Countries that we studied are all exhibiting different recovery rates. What factors influence recovery rates? Do some countries have an advantage over the other?
India has also crossed 20K cases. Are the same states still contributing to Indian cases or are there new states with high growth?
These are some of the questions we will try to answer in this article with the data that is available with us. And finally we will look at this week’s performance of states that we had identified as “Encouraging” states and “Worry” states in our last article.
But first we look at the CPM19 model Performance
CPM19 – On the Mark
The model has now caught the trend of all the 9 countries in study and for the last 3 days it has been predicting with almost 0% error.
The significance of this is that now we are able to predict daily growth rate and extrapolate the growth rate for the next 10 days with little error. We used this to look at the next 7 days for the countries in study and it definitely looks like all of them are on the path to recovery, except India.
The 42 day Theory – Update
In our last article, we had postulated the 42 day theory. (Read it again) All but the USA, India and Sweden had gone below the 5% threshold as on last update.
USA – US was on its 45th day and we had predicted it will go below the 5% threshold on the 48th day. It went below the threshold on 48th day
Sweden – Sweden was on its 41st day and we had predicted it will go below the 5% threshold on the 42nd day. It went below the threshold on the 42nd day.
So, for the USA and Sweden, our predictions were right on the mark. Also, we had postulated that once any country goes below the 5% threshold on a 7 day rolling average, they really slow down. That theory also seems to be holding true. (See table)
Except for Sweden which showed a slight increase on one day, all the other countries have shown a steady decline in their daily growth rates over the last week.
Unfortunately, the theory does not seem to be holding true for India. India is on its 38th day and with the current daily growth rate of India, we do not see India going below the 5% threshold till day 50. We are unable to predict beyond the 50th day for India as India has shown erratic trends recently.
On the 38th day, India stands 3rd behind USA and France in terms of seven day rolling average of the daily growth rate. With the trend seen in the graph India might breach the max mark.(See graph)
The Recovery Rate
Different countries are showing different rates of recovery, even though they may be on the same life cycle of the virus. We looked at various parameters to see if we could identify the reason for difference in recovery rates.
To begin with, let’s define recovery rate.
Recovery Rate = Total number of recoveries / Total number of outcomes (death + recoveries)
We analyzed correlations between various parameters and recovery rate. We also checked the correlation of these parameters with the average daily number of cases reported after the 100th case.
Test/Million – We looked at test/million as the first factor that may aid recovery and also may explain the number of cases. Surprisingly, test per million parameter had very poor correlation with number of cases and negligible correlation with recovery rate
Obesity Rate – We looked at the obesity rate of the country that is percent of people in the country who are obese. This had a strong positive correlation with the number of cases. This means that higher obesity rate resulted in a higher number of daily cases. There was also a moderate to weak negative correlation with recovery rate. Higher the obesity rate, lower was the recovery rate.
Overall Population Age – Average age of the population had no correlation with either recovery rate or cases reported
Percentage of population infected over 50 – Since age had no correlation, we looked at the percentage of infected out of total infected, that were over 50 years. This showed a strong negative correlation to recovery rate. If the percentage of infected over 50 years out of total infected was less, the recovery rate was higher
T Factor – We looked at the amount of tourists that visit the country. Our hypothesis here was that a popular tourist destination would be more susceptible to the infection. We indexed the tourists basis the total tourists that visited the country in 2019 and called it the T factor, This showed a strong positive correlation to the daily number of cases reported
CD Factor – We also looked at the Chinese Diaspora. We hypothesized that a higher Chinese Diaspora would mean more travel of infected population from China to that country, both business and tourist. This also has held true as there is a huge positive correlation between CD factor and daily number of cases reported
We take a look at the impact of these factors for each country.
India is green or light green on all the parameters except test/mil. This clearly shows in the recovery rate. India needs to take care that its %infected over 50 does not increase.
Also India’s total outcome percentage that is total cases that have had an outcome over total reported cases is very low (23%). So the recovery rate may fluctuate.
Italy has a medium obesity rate and high T factor along with a moderate CD factor. Italy is also a favorite destination amongst the Chinese. This was one of the factors for initial infection. The fact that 71.2% of its infected cases are above 50, it has a low recovery rate also
USA has a high T and CD factor. Combined with the high obesity rate, it has the highest number of cases. Also the high obesity rate and 50% of infected people being above 50 has led to its low recovery rates. The outcome percentage for the USA is only 16%. We still await results in 84% of the cases
We did not have the age of infected people in Iran so could not review the recovery rate versus age. Iran has low T and CD factors, however, we know from news report that the initial infections in Iran were from closer interactions with China, that rose exponentially because of a religious event in the area of the outbreak.
South Korea is the anomaly in our study with respect to Per Day Cases. South Korea has both a high tourist population from China and a huge Chinese Diaspora. But proper management of people inflow from China helped control the spread in initial days, though they did not ban travel from China. The latter increase in cases were attributed to patient 31 who was a super spreader. The source of that infection has never been identified but post that Korean administration did well to control the spread with aggressive contact tracing.
Spain also suffered a lot in the initial days of the outbreak. However it was able to stabilize the growth rate. With a high obesity rate and a high T factor it has reported moderate per day cases and its recovery rate is also moderate. This is due to a high percentage of infections being reported in those above 50. Also 49% of the cases still are awaiting outcome, so the recovery rate may fluctuate.
Germany has had the fifth highest cases worldwide. Most factors were poor or moderate. This has meant that Germany though has reported a higher number of cases has managed the infection well amongst the elderly. Infact, Germany was lucky as the infection came in the country through youngsters holidaying in Italy. Rigorous testing ensured that the asymptomatic cases were also identified so that they were not able unknowingly to spread the infection amongst the older population.
Due to a high T factor and its popularity amongst the Chinese, France has seen high per day cases. It has a low recovery rate also as the majority of infections are amongst the greater than 50. Outcome% for France is also low at 38% so there could be an impact on the recovery rate.
Everything was in favor of Sweden, except the fact that it has a moderate obesity rate and it has let the infection spread amongst the elderly. It has the poorest recovery rate and the outcome% is also very low so that recovery rate may further worsen. Sweden’s main concern is the spread of infection in old age homes.
With only 34% of the cases that have had an outcome, this might be a little early to be looking at recovery rates but this gives us a direction of things to come. We will continue to track recovery rates across countries.
India – 20,000 and beyond.
India has become the 17th country to go beyond the 20K mark. It has crossed that mark almost after 3 months since the first reported case. Let’s take a look at the daily growth rate of new cases after India reported its 100th case.
Although the trend is downward, it is not a rapid downward trend which is not resulting in a slow down for growth rate. India’s problem seems to be arising from the fact that new states keep emerging as growth drivers while not enough states seem to be slowing down.
We looked at which states contributed the most in the first 10K cases and then in the next 10K cases. While Maharashtra remained top in terms of contribution, Gujarat, MP and UP have taken over the top 5. These states are also growing at a much faster pace than even Maharashtra.
Story of the States
The Worry States
In our last article we had identified states that were a worry or were showing worrisome signs. The graph below shows their 7 day rolling average of daily growth rate since the last update
The good news is that Delhi has definitely slowed down and the growth rate has now gone below 5%. Rajasthan is also showing some slowing trends as the growth rate has just gone below 10%.
Gujarat, MP, UP and WB are the major cause of concern currently. All these states are trending higher than Maharashtra. Although, Maharashtra is slowing down its not slowing down fast enough. Since a high number of cases have already been reported in Maharashtra, a 10% growth rate also means around 500 to 600 cases daily in the current scenario.
The empty space above 10% tells the story here. All these states have now come below 10% and have stayed below 10% over the last 7 days. Haryana has joined Kerala in the below 5% club of 7 day average growth rate. Tamil Nadu also seems to be following suit. Karnataka and AP are two states that also need to slow down and get below 5%.
India’s Road To Recovery
The road to recovery is highly dependent on the UP, MP, Rajasthan, Gujarat, Maharashtra and WB.
These are also the most populated states of India. Except Rajasthan, they are showing a growth rate in excess of 10%.
Extreme poverty in these states means that they also have a huge migrant population.Residents of UP, WB and Rajasthan travel all around the country as migrant laborers which will put all the other states which have controlled the cases during the lockdown at risk.
Daily wage workers form an important part of our agricultural and infrastructural economy, keeping them under lockdown for a longer period will also be detrimental to our economy.
Unless these states show dramatic improvement May 3rd does not seem enough for India.
About the Author
Sanjeev Prakash is an Analytics and Marketing professional with more than 12 years of experience in Analytics, Data Management, Sales, Brand Management, Corporate Communications, Market Research and Customer Relationship Management. Sanjeev has an MBA from IMT Ghaziabad and a degree in economics.
More than 659,000 newborn babies die every year in India. It is the highest number of newborn deaths in the world. The country also accounts for twenty percent of all maternal deaths worldwide, with more than 150 women dying in India each day due to preventable causes related to pregnancy and childbirth. Concerns about maternal mortality ratio and infant mortality rate keep surfacing. Both remain unacceptably high and too much focus is put on childbirth itself and not the periods before or after. India is committed to reaching the Global Sustainable Development Goals and achieving its own national development goals. To improve the quality of care during the intrapartum and postpartum periods, in 2016 the Indian Ministry of Health and Family Welfare released guidelines for the standardization of all labor rooms. This was primarily to reach development targets on maternal and newborn mortality. The guidelines help states reorganize their labor rooms for maximum efficiency and quality service delivery.
Reading Dr Vikram’s post on “is-health-insurance-the-answer-to-indias-healthcare-woes?” made me think. Well, in the United States, despite healthcare being the highest capita spend of the GDP as per Organization for economic Co-operation and development (OECD) survey. But yet still we are unable to meet the healthcare needs of the population. That made me think – Is having insurance (private and public) the answer to India’s healthcare issues?
I would like to give my perspective whether we should invest heavily in insurance and the role of the government, based on my knowledge of Unites States healthcare systems.