Conversational AI is the quickest way to convert your leads into prospective customers. It has already built an enormous application space in the technology and marketing domains. Businesses are adopting voice-based assistants to enhance their sales efforts and increase the lead generation processes. According to McKinsey, AI has the potential to add between $1.4 to $2.6 trillion in sales for businesses worldwide.

Many well-known brands are implementing conversational AI in their business models to offer customers with personalized experiences. AI helps businesses to understand the intent of the customer while engaging in conversations with them. In the present time, customers have a variety of options to make purchase decisions. Businesses can further leverage the NLP algorithm to respond to customer intent in the form of text or voice. Conversational AI uses an ML algorithm to continuously learn customer behavior, their language based on the conversations and help generate recommendations to ease the customer’s product choices. This method can be achieved by using powerful intelligent chat platforms. The conversational AI must be well trained and computed before customer handling.  More customer-centric campaigns with marketing techniques coupled with product recommendations and predictive lead scoring can be used to drive sales and maximize revenue potential.

Customer-centric campaigns – Businesses now are more digitally-driven which is an added advantage in conversational AI implementation. Organizations’ websites have various customer-centric forms such as feedback forms, inquiry forms, subscription forms, etc which helps them to keep a record of all the data collected. And with the help of conversational AI, organizations can do predictive analytics and get insights in real-time to address the customers with more relevant products and services. Organizations can further segment the customers based on their intent by applying funnel analytics to get a more clear understanding of how their products and services are meeting their customer needs, a segment of customers’ desires, new innovations prospects are looking for and much more.

Market research – Many organizations do extensive market research before rolling out products and services in order to segment their target markets. Conversational AI eases their research analytics models by providing them with actionable insights and assistance on how to deal with various market segments. As conversational AI can automate repetitive tasks without human interventions the possibility of any error is minimal.

Sales enablement – The marketing and sales team collects hundreds of leads on a daily basis from several ongoing campaigns and sources. But only a fraction of them is capable of effectively utilizing the leads to final closure. Leads gathered need to be nurtured until the final sign-off. This process is wearisome but significant for the sales team in order to close a deal. It is widely observed that after an initial contact it takes 3-4 follow-ups by the sales team to get a response from the leads. One sales resource can reach out to one lead at a time which will be quite difficult for companies having big data. AI assistants can be integrated into any existing ERP and other databases to contact each leads in a personalized way and do multiple automated follow-ups using deep learning algorithms in order to qualify them as sales prospects within a short time span, unlike human representatives. These tasks can be easily automated using deep learning to close deals rapidly.

Customer relationship management – Sales CRM contains a wide range of leads information and quite often sales representatives are lost in those records while manually searching for lead details that lead to a loss of considerable time.  AI helps the sales team to dig up old leads collected way back and somehow fallen off track for not communicating proactively. Conversational AI when integrated with sales CRM provides deeper insights on leads’ intent, demography, and other information required by the sales rep to engage with them proficiently. One huge advantage voice-based assistants can provide here is that the sales personnel are not required to be wary of technical know-how to understand the insights provided.  They just need to speak in natural language with the tool and the NLP does the rest. The time and efforts saved by the sales representative can be productively utilized in communication with prospective clients to increase sales closures.

Predicting purchases – Predictive analytics and machine learning can predict customer purchases as the tool is consistently learning from human behavior and can alert the logistics departments about the deficiencies of required materials in their inventory well ahead of time in order to avoid any delay in sales. AI can track the movements of millions of customers on the website at once and decide the demand for definite products and services which encourages the sales team to come up with various promotions on those particular products and services.

Content selling – AI can analyze high volumes of data and track content engagement rates. This can help sales and marketing personnel to prioritize their follow-ups to provide personalized content to prospects at every stage of the customer journey and also share relevant content with the social networks thereby progressing towards a meaningful conversation and a fruitful conversion.  AI and ML can be a great support to the sales team in designing sales campaigns and promotions and allows them to offer feasible sales discounts. AI algorithms analyze past price data such as discounted figures, promotional parameters, and sales history and calculate the price elasticity for certain products and services so that the team can set prices optimally personalized to the customers.

Conversational AI not only reduces human efforts in tedious tasks but also helps the sales team to generate more revenue from the market.

The global artificial intelligence (AI) in agriculture market size is expected to be worth USD 2.6 billion by 2025 according to a report by Markets and Markets.  Agriculture is a major industry and plays a pivotal role in the economy of nations.  Population growth and climate changes have impelled the $5 trillion industry to look for sustainable and innovative solutions to improve growth.  AI has emerged as the industry’s technology arm

Agriculture is one of the most important professions for humanity. Irrespective of how the other sectors have grown, the demand for food has only increased. So, why not combine AI technology with agriculture and support both the sectors?  The rapid population growth and high demand for food combined with the scarcity of land certainly call for an efficient and effective method of farming to ensure better sustainability.

There are several terabytes of data from farms.  With the help of AI technologies and the Internet of Things, farmers can analyze real-time data on weather conditions, soil, temperature, and so on.  AI technologies also help in optimizing planning and utilization.  Farmer’s Weekly Magazine states that the use of AI-powered equipment based on the computer vision technology increases crop yields by about 30% and enables to predict weekly and seasonal crop yields with more than 90% accuracy.

The quality of crops can also be improved by identifying infected plants. Improving harvest quality and accuracy using AI systems, known as Precision agriculture technology, has been known to detect crop disease and pest damage with 98% accuracy with the help of GPS(  Global positioning system) and GIS (geographic information system) Guidance systems.  AI sensors can detect and target weeds and then decide which herbicides to apply. This not only reduces cost but also prevents excessive toxins that find their way in our food.  VRT (variable-rate technology) is automatic and can be used for a variety of farming activities. It sets the delivery of inputs depending on the soil condition noted by soil maps. Also, Rate controllers are used to control the delivery rate of a chemical (liquid/granular). These control speed, flow rate, and pressure of material in real-time.

Digital Soil mapping is a geographic representation showing the diversity of soil types in the interested area. It helps one determine what land use management will be sustainable at a particular site. These can estimate weather, soil conditions, temperature, and water usage to make better decisions. Farming can be made more cost-efficient by ensuring only the required inputs are used.

A yield map can be used to compare yield distribution within the field over a period of time. This allows farmers to know which area of the field needs improvement. With this, they can change their field management technique and develop nutrient strategies too. These yield records can support as proof to avail farmer loans.

(source: United states department of agriculture, economic research service)

Though all of this seems like a farfetched idea in a developing country, it has experimented. Large scale farmers use machinery for areas as large as 30 meters. However, the precision application of fertilizers and pesticides can be done in an area of 5-10 meters. Hence it will be only a one-time investment in the technology with better yields in subsequent times.

The swift increase in the outbreak of coronavirus across every nation is pressing its capabilities in medical care and a reminder to us that health transcends all borders.  Countries recently started slow adoption of artificial intelligence in their healthcare industries but with this pandemic, they are accelerating this adoption curve because the number of casualties is greater than the number of medical resources available. Due to these scarce resources governments of various countries are calling for a nationwide lockdown to limit the number of the virus spread. Countries like Iran, Pakistan, Italy, Poland, Africa and others currently in the developing stage, are facing multiple healthcare challenges in this fight against coronavirus.

Medical data collected is too huge for human intelligence to handle this is where AI plays a pivotal role. AI is trained to identify and understand patterns from big data and acts as a trump card in saving the entire humanity from this crisis.  With the help of AI, medical facilities can effectively use their limited essential supplies & medical staff to contain a situation like COVID-19. AI can predict the sudden increase in demand on healthcare services which will help them know what services are required to treat the infected patients.

Artificial intelligence is a key resource in healthcare as it can reap actionable insights from huge amounts of medical data, predict the trends, patterns of the virus spread and can make important decisions that can save millions of human lives in different parts of the world.

Hospitals are using AI to screen and classify infected patients and also identify the ones who are most likely to develop coronavirus symptoms. AI-powered cameras and drones are being used by the medical staff to scan the faces to check the temperature by maintaining a social distancing because of the virus’s ability to communicate through physical contact. In today’s world, the majority of the tech-savvy people are using gadgets like fitness tracking watches or apps related to physical monitor. AI can track these data, learn about the person’s health from the data and help identify potential people that can easily get affected or are already infected from the virus based on their health score. Medicals, as well as health tech companies, are predominantly using AI in their regions to identify infected people, people came in contact with infected people and also tracking the medical supply chain to stay alert about the usage & reduction in the health supplies in coming time.

AI applications in healthcare are not limited only to the patient’s health conditions but also for the health workers who are fighting their day and night to treat the patients to end this pandemic. Researchers in the San Francisco’s University of California are using Oura’s wearable rings designed using AI to track COVID-19 symptoms in the health of the healthcare workers. It captures the early symptoms of the illness especially for the healthcare workers who are high at risk of contracting the virus.  The AI algorithm in the ring measures primarily two signs that include elevated heart rate & temperature above 99.1 degrees Fahrenheit so that hospitals can isolate those workers for the operations & provide them with proper medical care.

Healthcare professionals around various nations are now switching on to AI capabilities to find a cure against this deadly virus. While the global pandemic outbreak is increasing the number of confirmed cases and the number of deaths across nations, many biotech firms are creating drugs to target the virus; thanks to AI, AI is helping firms and scientists find a vaccine. Vaccines imitate an infection, causing the production of defensive white blood cells and antigens.  AI is not only suggesting components of a vaccine by understanding protein structures, but it is also useful in the development of subunit and nucleic acid vaccines.

Data scientists are using machine learning to screen for antibodies that can kill coronavirus with the highest success probability score. Unlike the traditional way of discovering antibodies in the labs that take years of experiments and trials before finding the right one, machine learning algorithms can identify antibodies that can beat the virus in a matter of weeks reducing the time and cost associated with it.  AI is accelerating the development of antibodies and vaccines with the help of ML that can scan through various existing drugs to see if any of the molecular compounds in those drugs can be reused with a mix n match with other drug compounds and develop a drug to fight the current as well as the future outbreaks. Nine potential drugs have been identified by an AI-platform out of which six are already approved in many countries are being used by doctors to treat the infected patients helping to recover fast.

Conversational AI is being used by some of the healthcare companies to provide quick information about COVID to the public hence making the work of a doctor much easier in delivering the severities of contracting the disease. The information is gathered from several websites and social media channels. The conversational AI engine is trained using information collected from authorized sources to give accurate results. Deep learning is used to study information available in an unorganized/unstructured format. Here conversational AI isn’t a replacement for a doctor but it aids them to stay updated about COVID developments. Conversational AI can learn quickly and pick up buzzwords related to the objective more briskly than any other technologies & also it provides real-time information that helps the public to stay up-to-date about the outbreak news.

AI is integrated into various healthcare systems, machines & devices to empower it with the automation with a maximum level of accuracy. If AI is engineered and trained with more quality healthcare data including MRI & CT scan images, it would be easier to predict & combat such deadly diseases in the future.

The coronavirus started in Wuhan city of China. The first positive case in India was recorded on 30th January 2020.  It took almost 3 months to reach 100 cases. At the current rate, it is predicted that the ‘ending phase’ of the spread in India should start from May 9.  Japan saw a 13% daily increase in cases before reaching 100 cases and an 8.1% daily increase in cases from its 100th case to its latest. change in daily average cases was lower after the 100th in China, Singapore, South Korea, and Japan than before. They appear to have successfully flattened their curves compared to western Europe, the US, and India. As of April 14,  11,438 cases have been registered out of which 1305 have been cured and 377 have succumbed to it.

(Source: https://www.statista.com/)

A recent poll conducted by us on the expected outbreak of the virus in India showed that 61% of people anticipated an uncontrolled outbreak in India while the rest thought otherwise or have no clue about how the outbreak will go.

However, global reports state that the nation has one of the lowest numbers of COVID-19 cases per capita in the world.  5 out of 1000000 have been the reported cases in India while in the US and Italy it has been over 1000 and 2000 respectively.

A country with more than 1.3 billion population is supposedly doing better than the other countries in handling the COVID-19 spread by imposing severe measures to contain the virus spread including a nationwide lockdown declared for a period of 21 days on 24th March 2020 with essentials and medical facilities operating on a restricted time frame on a daily basis.  Working from home, social distancing, lighting lamps, whipping coffee and digital entertainment have kept us going!

The end of the lockdown period raised many questions on the minds of people. 80% of the political parties requested the central government for an extension while a few people also demanded the same by using the hashtag  #extendthelockdown when Tamil Nadu, Delhi, and Maharashtra announced a complete lockdown till the 30th of April.

On 14th April, the Prime minister extended the lockdown to 3rd May 2020 to combat the crucial stage of the spread while indicating that in safe areas, small scale economic activity might resume after the 20th of April. India has also placed travel restrictions relatively early with many states shutting off access to public places and intercity travels.

For a highly populous country, a stage of unattended community spread would be a disaster on socio-economic and political terms. Only strict adherence to government guidelines can ensure this situation does not escalate further.  The lockdown is paying off by slowing down the spread. Compared to other countries that were slow to impose the lockdowns, India has taken an extreme measure to lockdown the entire nation that is helping control the situation.

However, the country’s high population density, overburdened public health, and the possibility of transmission from younger people (50% of the population below the age of 25) to the elderly in joint families are worrying factors.  India’s GDP decelerated to the lowest in over 6 years in the 3rd quarter of 2019-20., and the outbreak of COVID-19 has posed a fresh challenge. The Abrupt cease of economic activity will drop the demand for non-essential goods. With further supply chain disruption, even the availability of essential commodities might get affected. (source: KPMG)

According to  a study, A peak in new cases is expected in week 3 of June and a potential or actual  lift of lockdown between week 4 of June and week 2 of September [source: John Hopkins University (Coronavirus Resource Center), BCG Analysis]

Agriculture, trade, education, and livelihood of daily wage workers are just a few things that have been impacted and/ or come to a standstill. Decisions to tackle the slowdown caused include better wage schemes under MGNREGA, free cooking fuel, increased pension for senior citizens and free medical insurance for medical staff.

Railway services were supposed to resume after lockdown and all tickets had been booked already. Nevertheless Fear of a rapid spread post lockdown is still fogging the minds of people.  The lack of certainty with regard to transport and work is also getting exasperating with various ideas on people’s minds at the moment. While many believe India has handled it better than any other country, some fear that the worst is yet to come. When humans are being defeated by the virus,  With the help of AI and other technology in medicine, governance, and finance we can certainly overcome these testing times.

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NEED FOR AI  IN TRAVEL INDUSTRY, WITH REFERENCE TO COVID-19

Every sector is anticipating a dismal future. Even in these gloomy times, AI can help us float the boat. In Wuhan, where the virus originated, China facial recognition software linked to a mandatory phone app that color-coded people based on their contagion risk, decided who could enter public spaces. Even before such technology was implemented, BlueDot, A Canadian AI start-up, alerted about unusual pneumonia around a market in Wuhan in the month of December.

With the growing middle class and an increase in disposable income as a result of easy credit availability, the travel and leisure industry has benefited the most. However, The COVID  pandemic has affected the regular lifestyle of many. This sector stands most affected. In China, international travel was suspended even for those holding a valid visa.

Travel is a consumer-oriented service. AI can help understand customer needs in order to enhance loyalty as well as profitability. Conversational AI can be employed on social media platforms where the customers provide their feedback.  Chatbots can also be used to handle customer queries to make the process hassle-free. online customer service could also be enhanced by the same.

Traveler’s behavior and needs (most traveled regions, age group, gender, etc) can be understood with the use of heat mapping and travel service providers can target their marketing accordingly.  Facial recognition can ensure that tiresome paperwork is gotten rid of.  This way people can easily move through airports and other transport centers.

Machine learning can use external data and customer behavior to provide suggestions to the customer based on the same. For instance,  a change in climatic conditions can result in a change in travel plans. This can be managed by AI for the customer.

Travel is not only about customer satisfaction but also sustaining in the market.  When Jet Airways quit the market, the vault created for customers had to be filled by other airline service providers. In such a situation predictive analysis plays a key role In understanding competition and customer churn rates. Each airline could have predicted market conditions earlier and developed itself to serve the situation.

India was having slow economic growth even before the pandemic. To tackle the fall in aggregate demand, artificial demand had been created in various sectors. However, at this moment supply is stagnant due to the virus outbreak. Such a situation could also be tackled with predictive analysis.  Even when the virus began to spread earlier this year, reduction in travel was certainly foreseeable. Ways to sustain employment could be discovered beforehand by predicting customer trends with AI.

(Source: https://www.statista.com/)

As the total number of COVID-19 reported cases reaches 1,358,469 as of 7 April 2020. And countries like Spain & Iran reported 3835 & 2089 number of reported in one day, countries across the globe are trying their best to combat this crisis. Several countries including The US, China, South Korea, Taiwan are implementing AI-based solutions to combat COVID-19.

AI can not only predict the start of an epidemic but can also forecast how it will spread. Quick response, prediction, and prevention help stalling outbreaks of epidemics such as the COVID-19.  Natural Language Processing, Machine Learning, and genetic applied science can successfully study travel patterns, traveler data, health organizations data, climate data from satellites and more to provide new insights to address the outbreak and help contain the devastating effects.

The role of AI becomes more relevant to contain the spread of the disease COVID-19 because of its technological developments and innovative techniques.  AI helps in predicting the flow of the virus by drilling deep into the data collected.

So, what kind of data is needed for AI to predict the flow and pattern of COVID-19 across the countries? Data such as clinical and travel data helps the researchers to a great extent to predict the pattern of COVID-19 flow. There are also personal data that will be of help to analyze the affected status from social media channels such as their lifestyle, eating habits, family history and more.

From early detection of coronavirus to tracing the contacts, providing analytics on collected data from various sources, developing vaccines, AI plays an important role in fighting COVID-19 globally. Doctors and Governments are now using AI to trace the people who came in contact with the infected patients, to isolate and monitor them for symptoms to help stop the spread. There are various analytics techniques that are available to generate actionable insights to better study COVID-19 & fight against it. A few of them are described below:

1. Path analysis – It helps to visualize the flow of coronavirus in infected patients. It projects in detail how the disease is progressing across a particular demography. Medical data of a region like daily reported cases, active cases, number of deaths & recovery are taken into account to do path analysis.
2. Graph analysis – This analysis generates insights on the COVID-19 outbreak to predict the spread among the local population. A detailed analysis further identifies the super spreaders’ or events where the infection was super-spreading among the people. In the graph, analysis forms a network map that projects the degree of interconnectedness between infected cases & the contacts. Each junction represents an infected person wherein the edge represents the channeling of the infection through contact.
3. Telco analytics – This refers to the analytics done with the data gathered from a person’s electronic devices such as mobiles, tabs, smartwatch & other electronic accessories. The electronic devices not only possess the personal data right from the name, age, gender, to GPS data collected both present & previous locations, to browsing patterns and much more. A lot can be analyzed with the GPS data including travel history & mobility patterns. The best thing about telco analytics is it is capable of providing real-time insights about an infected person’s activities who are referred to isolation or the suspects who are advised for home quarantine.

The applications of AI/analytics does not stop here. Researchers & therapeutics are betting on AI to discover potential COVID-19 medicines. AI is used to identify molecular compounds in the test data that can be as promising as to go for detailed testing in the labs within a few weeks of its discovery, unlike the conventional way where a team of scientists takes years of several experiments testing the chemical compounds in an effort to develop a new drug. Neural networks are used to accelerate the drug discovery process as they can run through the huge molecular data set & identify the required attributes to develop a new drug. NLP is being used to remove the texts from thousands & thousands of sources to cleanse news & statements made by representatives about the health of living beings.

Countries are broadly relying on AI applications to combat this infection because of their fast learning cycle, generating key insights & accuracy in forecasting from the collected data. AI is capable of learning both structured and unstructured datasets available anywhere in the sources. But one of the main challenges here is the availability of appropriate data by the government. A lot of manipulation happens in the data before it makes public in order to control the panic rising among the citizens. There are lots of open sources from where the data on coronavirus cases can be reaped using AI. Many AI-based firms are now developing a deep-learning-based model for automated detection COVID-19. The model is trained with chest CT scans images of COVID-19 infected patients from several hospitals treating COVID patients.

AI-powered chatbots are now widely being used to provide information about COVID-19 symptoms, do’s & don’ts during quarantine period & many more. Organizations like Facebook in association with the Indian government and national governments around the world are building chatbots to help people get accurate and timely information about COVID-19. They have also tied up with the World Health Organization (WHO) to get authoritative information about coronavirus directly in the WhatsApp inbox to help fight misinformation amid crisis. Real-time insights on daily reports about COVID-19 cases are being sent using this chatbot. Many healthcare tech industries are developing chatbots for people to go through self-assessment about COVID-19 symptoms. There are a set of parameters given if selected accurately the chatbot further guides the user if it requires to get admitted in hospital or home quarantine is applicable. The primary objective of a chatbot is to provide real-time information of COVID-19 cases, fight the fake information over social media handles & other sites, creating awareness & self-assessment of COVID symptoms.

Singapore hospital & public health facility are performing real-time temperature checks using smartphone & thermal sensors. China is using an AI system that uses sensor & AI to predict people’s temperature, this system can check the temperature of around 200 people per minute. The systems send an alarm if it detects a person with a temperature above 99.1 degrees Fahrenheit. Drones are being used to supervise people under home quarantine, thermal sensing & spraying disinfectant. As soon as South Korea’s government permitted private sector companies to begin developing coronavirus testing kits, a Seoul-based molecular biotech company used AI to accelerate the development of testing kits.

There is a race to find medicines and treatments not only in various AI tech companies & but also in between various countries like the US, China, South Korea, and Israel. Although every country in the world has adopted personalized approaches to end the disease, they are extensively using AI, Big Data & Data Science among various other technologies to combat COVID-19.

You can also help your country in this fight against coronavirus by regularly washing, sanitizing your hands, avoiding contact with any parts of your face and most importantly by maintaining social-distancing & avoid going out unless it is really necessary.

COVID-19 is a bio-war against humanity that has its origin in Wuhan, China that started way back in December 2019, declared as “Pandemic” on 11 March 2020 after it infected approximately 1,118,245 people across the world as on 3 April 2020. India is also grappling to combat this virus spread by adopting various measures from time to time including lockdowns and border shutdowns.

A major outbreak in the country is likely to have a far-reaching effect if not contained at this stage.  As the nation gets ready to combat the outbreak, let us have a look at what the data reveals on the pandemic in relation to the Indian geography.

A graphical representation of Date wise COVID-19 cumulative reported cases

source:www.covid19india.org

India reported its first COVID-19 case on 30th January 2020. As of 3rd April 2020, the Ministry of Health and Family Welfare has confirmed a total of 2902 reported cases (Source:https://www.covid19india.org/). Although the testing rates are comparatively lower as compared to other countries in the world. As per reports, the COVID-19 infection rate in India is reported to be 1.7, lower than the rate in the worst affected countries.

India is witnessing a steady increase in the number of cumulative reported cases.  From 3 March 2020 (6 reported cases) to 4th March 2020, there has been a sudden spike in the numbers from a single-digit 6 to double-digit 28. India continued reporting 2-3 cases per day which is much lower than the daily reports of other countries. On 14th March 2020, India COVID-19 reports crossed 100 when the union government declared the pandemic as a “notified disaster” under the Disaster Management Act, 2005.

Indian Prime Minister Narendra Modi imposed a ‘Janata curfew’ on 19th March, during a 30-minute live telecast, asking all citizens to observe “Janta Curfew” on 22 March from 7 AM to 9 PM post the steep increase in the reported cases. Following this one-day lockdown, many states & union territories started implementing state-wise lockdown till 31 March. A 21-day nationwide lockdown was announced on 24th March by Prime Minister Narendra Modi as a preventive measure for combating the outbreak.  The outbreak has been declared an epidemic considering the growing number of reported cases and when the transmission escalated from 24th March to 3rd April 2020. Ever since then, the numbers are alarmingly increasing in the country.

State/UT wise cumulative reported cases

Inspite of the lockdown in place, the total number of reported cases is increasing almost every day. Maharashtra, Tamil Nadu & Delhi are witnessing the worst COVID-19 reported cases 490, 411 & 386 respectively as on 3rd April 2020. New Delhi is expected to get affected by more numbers in the next 1-2 days. The surge in the numbers is due to participation by the people in a religious congregation in Delhi in early March.

About. 1830 people across India attended this event which included 281 foreigners who stayed put there till 8 March. Many people who attended the event started showing symptoms in late March which is when the news of this event came into light. In Delhi, around 53 people have tested COVID-19 whereas Tamil Nadu reported more than 190 cases in a single day followed by Assam, Arunachal Pradesh that has reported 5 & 1 new cases each.  Telangana government has declared 6 deaths and all of them have been to this event.

Date wise death reports

State/UT wise death reports

India has confirmed 68 deaths as of 3 April 2020. The number of deaths increased two-folds in the last 4 days crossing 40 plus. Maharashtra has witnessed the highest death counts among all other states/UTs touching 26 as of 3 April 2020. People who died of COVID-19 in India had other underlying chronic diseases along with coronavirus. A total number of 229 patients have recovered so far which brings the total active cases to 2673.

Two of the major challenges for the government is trying to overcome is the scope of tracking people with international, national travel history and the supply of medical essentials like ventilators, masks,hand-sanitizers, ventilators, COVID specialized ICU units, etc.

In a study earlier this week of data from 332 reported cases and population statistics from data.un.org, the majority of infections were in the 20-29-year age category amounting to 28.9%. This group had imported cases, carrying from the infection from traveling abroad.

The 30-39-year category amounted to 20.5% that also had a lot of imported cases.

While the central government has improved the health indicators, immunizations, etc, and some states like Tamil Nadu, Kerala and Karnataka have a comparatively better health system than the other states, it is important to contain the spread and impose diligent measures for the same.  While social distancing, stay home are imposed, it becomes equally important for citizens of all age groups to take responsibility to provide support to the nation in terms of combating the outbreak by following the same while healthcare workers are enhancing their approaches to contain the virus spread.

As per statistics on 31st March 2020, the global coronavirus cases have touched 884,921 (worldometers.info). It all started on 31st December 2019 when WHO China was informed of cases of pneumonia because of an unknown cause. The total number of reported cases reached 44 on 3rd January 2020 and on 7th January 2020, Chinese authorities identified a new type of virus, the coronavirus. On 20th January 2020, China reported 278 confirmed cases and 6 deaths from the city of Wuhan, the epicenter of the pandemic, home to 11 million inhabitants. The evacuation process spread the virus to many people from China to various countries.

A look at date wise charts to show the spread of Coronavirus in China, Italy, Iran & the US, the top countries of the major outbreak is represented in the charts below

The article throws light on the jump from stage 1 of the virus spread where the cases are imported from affected countries to stage 2 where local transmission happens to stage 3 of community transmission.  Stage 4 has clusters of infection, China has been in stage 4.

The graphs represent the spread of the virus since its first outbreak in the respective countries. While the first outbreak in China happened on 31st December 2019, Italy reported its 1st on 31st January 2020 & Iran on 19th February 2020. The outburst in the four countries is much more compared to the other countries. While in China the spread was increasing twofold every second day, Italy faced a rise in almost 2 weeks of the outbreak. If the dates are to be analyzed, the outbreak in Italy happened very late after the outbreak in China but the increase in the number of cases reported is similar to China. Even in the US, the number of reported coronavirus cases is shockingly huge in two months of its outbreak currently standing at 189,612.  But the majority of the countries reported as low as 2 positive cases in stage 1 of coronavirus pandemic. Stage 1 indicates the stage where the infection is only limited to those who have traveled to virus hit countries and have tested positive.

As China grappled with the pandemic outbreak that seemed out of control, it seems to be leveling off in a matter of 2 months. 15th March 2020 marked a statistical milestone date when confirmed cases of COVID-19 outside of China surpassed the Chinese total.

A detailed day-wise study for 2 months, of the number of reported cases, in a few selected countries including India, shown below to better understand how countries are fighting against the virus spread:

The table above describes the spread recorded in a timeline of 5 days to do a comparative study to better understand the flow of the virus. For each of the countries, day 1 may vary depending on the date of the outbreak.

China reported the highest number of cases on the very first day of the coronavirus outbreak whereas other countries reported a maximum of 1-2 cases each. Other than China, where it all started, the rest of the cases were imported into the countries through an already infected carrier. Iran shows the highest rise in the number of reported cases in 10 days to 388 as compared to any other country.  China the epicenter of the pandemic shows a rise in the number of cases to 278 after 20 days.

Italy saw a steady increase in the number of cases but after a month the numbers jumped to a whopping 2000. Since then the number has been alarmingly increasing in the country and stood at 10149 at day 40. Reason?? No early measures to contain the spread or isolate the virus or limit the movement of the people. After China, Iran is the most affected as the numbers increased to an exploding 14991 on day 50 from 4747 on day 40.

Almost a month after Iran got hit by the pandemic, the number of reported cases reached 24811, almost touching the US’ number at day 60. Even after observing Italy’s situation, Iran failed to take early steps to control the virus spread. The number of officially reported cases has doubled almost daily and at least 3,036 people have now died, according to the latest official figures. As per sources, the officials tried to hide the outbreak of the virus to the country by stating that it’s like normal flu.

While the impact of the novel coronavirus has been the most in China and Italy, India also is within its grasp.  India reported the first case on 30th January 2020 in Kerala. The government has announced a 21-day lockdown until April 14, 2020, identified 20 existing and 22 potential hotspots to prevent the widespread transmission. The epidemic has expanded its footprint in the country, affecting 1,347 people till 31st March 2020 and the trajectory of the disease is going to be unclear.

Table below depicts states & union territories wise reported cases in India

Maharashtra and Kerala reported the highest numbers of coronavirus cases with 325 & 241 respectively. Even before the Government announced the complete lockdown, many states in India have already implemented a state-level lockdown to curb the numbers, sealing their borders from their neighboring states to ban all kinds of transportations. As per reports, India is at stage 2 of the COVID-19 outbreak even after two months of its first case reported.

In the US, where the numbers are overwhelmingly increasing at the rate of 1000s every 5th day, reported cases as of 31st March 2020 stood at 140640. President Donal Trump is endorsing the end to coronavirus social distancing soon and announced in a news conference that “America will again — and soon — be open for business,”. In developed countries like the US which has 2.8 hospital beds per 1,000 people, at a 10% hospitalization rate, all hospital beds in the U.S. are predicted to be filled by 10th May 2020. If 20% of cases require hospitalization, there are chances that the US might run out of beds by May 4. Deaths have been in devastating numbers mostly because of unpreparedness for the pandemic followed by a limited number of doctors operating per infected person & lack of medical treatments.

Because of the inverse relationship between the number of infectees & medical facilities including the number of doctors, nurses, medicines the death rates are also increasing globally. The graph below is a comparative death analysis among several countries like China, Japan, The US, Italy, Canada, Iran & India.

China has seen great losses in human lives right from the beginning of the outbreak by approx. 3,287. Italy surpassed the death rates of China in two months of the outbreak in the country by 7,503. The US has also crossed 2000 deaths as on 31st March 2020 followed by Iran witnessing 222 deaths as on the same date. Countries like Canada & India have experienced 58 & 33 deaths respectively. In China, where the population is approx 1,427,647,786 the death rate is comparatively invincible than the countries like the US, Italy & Iran which has a population of 327,096,265, 60,627,291 & 81,800,188 respectively. Whereas India whose population is 1,352,642,280 almost equivalent to China, the death rate is considerably lower than all the countries listed above (Source: https://en.wikipedia.org/wiki/World_population).

 

What is interesting here is China, the epicenter of the pandemic is experiencing a sudden dip in the number of deaths in China. If one can compare the number of new deaths on 20th March 2020, China stands at 8 new deaths compared to what was observed on 5th March 2020 (31 new deaths) wherein countries like Italy touched 625 highest number compared to what was recorded as on 5th march 2020 (27 new deaths). 

 

This leads to a very interesting question. Was China already prepared for this pandemic ever since its reporting in Wuhan? Or China is internally fighting this virus without letting the information come out of the country? 

As China prepared itself as the virus started rolling, they started constructing makeshift medical facilities on 24th January 2020 with 1,000 beds that became operational on 3rd February 2020. There are a lot of speculations building around this sudden fall in the death rate in China while the numbers are increasing rigorously in other countries.

 

The mishandling by the government of China on the coronavirus outbreak that began in Wuhan province by initially trying to cover it up. They started detaining the doctors who raised early alarm bells to make other countries aware of the spread of the pandemic. But now, as cases within its own borders begin to rise, Beijing is shipping sorely needed medical supplies and their doctors worldwide, including to Italy and Iran, two of the countries hit hardest by the virus outside of China. 

 

In these three months since the virus began its deadly spread, China, Europe, and the United States have all set off at a sprint to become the first country to produce a coronavirus vaccine. The World Health Organization officials say they are working with scientists across the globe on at least 20 different coronavirus vaccines with some already in clinical trials in record time.

 

Countries like China & the US are using advanced AI to help diagnose the disease and accelerate the development of a vaccine. AI is also being used as a surveillance system to keep a tab on infected individuals and enforce quarantines. Tech companies across the globe are implementing AI to track the virus & predict the outbreaks to process healthcare claims. AI-powered chatbots are also being used to deliver real-time information about the coronavirus pandemic. AI is learning every implementation during this hard time to aid research and vaccination.

Note: The numbers of reported cases & the number of deaths are subject to variation depending on the numbers reported.