Data Scientist Says California and New York May Have Achieved Herd Immunity
Sun, April 18, 2021

Data Scientist Says California and New York May Have Achieved Herd Immunity


A data scientist said that California and New York may have attained herd immunity against COVID-19. Via a unique computational model, the scientist found a steady decrease in mortality in both US states.

The possibility of herd immunity in California and New York was revealed by a data scientist at Ben-Gurion University of Negev (BGU). They believed that herd immunity might have been reached in these states. The computational model used reflected two things: the steady decline in mortality and the basic reproduction number below the social distancing guidelines. If no new unusual outbreaks develop, the infection rate in those states would continue to decline.

Herd Immunity in COVID-19 and Other Infectious Diseases

Herd immunity is a phenomenon wherein the majority of the population is immune or resistant to infectious diseases. Normally, this can happen if a population group contracted and recovered from a disease. But this method can risk many people to complications and disability. Sometimes, those who recovered suffer from permanent damage in one or more organs. While others have immune systems nearly wiped out, making them vulnerable to other infections.

Vaccination mimics the natural method in a significantly less risky manner. Vaccines expose the human body to a killed or weakened pathogen to trigger an immune response. This enables the immune system to arm itself before the real infection. However, vaccines do have certain dangers including allergic reactions and adverse effects in people with compromised immunity.



To balance the downsides, herd immunity is promoted by vaccinating the majority. If 90% of the population of a city is vaccinated, the remaining 10% are protected from infectious diseases. The immunization of most people can make it difficult for pathogens to reach those who are susceptible.

According to Our World in Data, an online source of research data, measles and pertussis have the highest herd immunity threshold between 92% and 95% of the population. These are followed by diphtheria and rubella with a threshold between 83% and 86%, and polio with a threshold between 80% and 86%. Mumps has a threshold from 75% to 86% while influenza has a threshold from 33% to 44%. The threshold includes the calculation of basic reproduction number or R naught. The higher the number, the greater the threshold is needed to achieve herd immunity. Both measles and pertussis have a minimum R naught of 12.

Meanwhile, the herd immunity for COVID-19 is still far from the minimum threshold of 60%. Statista, a German portal for statistics, showed the estimated share of the population of COVID-19 antibodies in various cities. New York City had a share of 19.9% as of May 2, 2020, London had a share of 17.5% as of May 21, 2020, and Madrid had a share of 11.3% as of May 13, 2020. Wuhan, the original epicenter, had a share of 10% as of April 20, 2020, Boston had a share of 9.9% as of May 15, 2020, Stockholm had a share of 7.3% as of May 20, 2020, and Barcelona had a share of 7.1% as of May 13, 2020.



COVID-19 Herd Immunity in California and New York

At BGU, a data scientist believes that two US states already achieved herd immunity for COVID-19. While the effects might not be obvious to many, the mortality rates in these areas have been declining consistently. That decline could be empowered by specific steps to influence the infection rates. However, unusual outbreaks could cancel the improvements depending on the main cause. As such, monitoring case clusters in schools and places where mass gatherings could happen must be done.

The findings are derived from the SIR model of Infection Dynamics. The SIR stands for susceptible, infectious, and recovered labels. The model can determine COVID-19 scenarios using population data and assigning details in those labels. It can also show how the interventions from public health agencies influence the flow of epidemic.

For the State of New York, the SIR model predicted near herd immunity in late June 2020. The disease was defined with R naught of less than one. The model showed a consistent decrease in reported deaths due to COVID-19 from that period. If compared, the R naught in late June is below the R naught of 1.14 in social distancing restrictions. That indicated that an infected person could spread secondary infections of less than one, on average. In that same period, the state had about 400,000 confirmed cases. It implied 2.4 million actual infections based on serological test results performed.

For the State of California, the herd immunity was likely reached on July 15. There was also a consistent decrease in mortality. The R naught was found below the 1.1 in the current restrictions. The model highlighted the herd immunity in 4.05 million individuals or over 10% of the state's population. The model's estimates were close to the numbers in Israel.

Israel might achieve herd immunity soon if the current trend persists. If the current restrictions were followed, the model predicted the upcoming end of the peak in cases. That was predicted to occur in late August or early September. But a total of 1.16 million people with COVID-19 antibodies must be achieved to attain herd immunity. Presently, the figures have been found close to that target number.

"We are heading in the right direction, but it is important not to relax our restrictions or get overconfident," said Professor Mark Last at BGU, quoted Medical Xpress, a medical and health news site.

Prof. Last cautioned about further restrictions and new outbreaks. Lockdowns will no longer aid in reducing the spread. The public simply needs to adhere to restrictions to support the decline in cases. If everyone follows, it will ease the suffocated healthcare sector. This is applicable to all nations. On the other hand, outbreaks have to be identified quickly if restrictions are eased. An unusual spike in new cases represents clusters.



School openings and mass gatherings defy restrictions. These are excellent pools of new outbreaks. Scientists may not show it but they are concerned about new strains of SARS-CoV-2. It is a virus and can mutate based on external factors. By following restrictions, people are also lowering the odds of a dangerous strain to spawn.