Asymptomatic, Presymptomatic, and Symptomatic Transmission
[Publication date of latest article cited: August 27, 2021]
People with SARS-C0V-2 infection, but without symptoms, probably cause much of the transmission to others., especially in households (Centers for Disease Control and Prevention “Scientific Briehttps://doi.org/10.1001/jamainternmed.2021.4686f: Community Use of Cloth Masks”; Joseph; Lee E, Wada, et al.; Wang C, Prather K, et al.). Epidemiological investigations in Chicago (Ghinai, Woods et al.), China (Bai et al.; Bi et al.; Columbia University; Du et al.; Ge et -al.; Li C, Ji, et al.; Li F, Li Y-Y, et al.; Li R, Pei, et al.; Pan X, Chen, et al.; Wang Y, Tian, et al.), Germany (Rothe et al.), Japan (Nishiura, Kobayashi et al.), and Singapore (Wei WE, Li Z et al.; Yong SEF, Anderson et al.) of patients’ contacts with other people found many probably received infection from asymptomatic carriers or presymptomatic patients. Many infected people with few or no symptoms shed as many viruses as symptomatic patients (He et al.; Lee S, Kim, et al.; Zou L, Ruan, et al.).
But symptomatic cases transmitted to more people than asymptomatic cases, according to surveys of Wuhan households (Li F, Li Y-Y, et al.), Luxembourg (Wilmes et al.), and Japanese clusters (Nakajo, Nishiura “Transmissibility”), systematic reviews and meta-analyses of many studies (Madewell et al.; Thompson H, Mousa, et al.; van Elsland; World Health Organization “Advice on the Use of Masks”), and contact tracing studies (Sayamphanathan et al.). For example, in two studies in China, symptomatic cases were 4 times and 10 times more likely to transmit than asymptomatic cases (Ge et al.; Li C, Zhu Y, et al.). During the early months of the pandemic in the US, symptomatic patients infected 29% of their household contacts (secondary infection rate, SIR), including 42% of their children and 33% of spouses/ partners (Lewis NM, Chu VT, et al.).
Several studies found large percentages of people had asymptomatic infections, varying with their ages and transmission situations (Oran, Topol). For example, a longitudinal serological survey of the first epicenter, Wuhan, China, showed that 82% of those with antibodies had been asymptomatic (He Z, Ren, et al.). A survey of half the Luxembourg resident population found 33% of positive cases were asymptomatic (Wilmes et al.). In the heavily infected Italian town of Vo, testing most of the population twice found about 40% of infected people had no symptoms, and the symptomatic and asymptomatic cases had about equal viral loads that could transmit to others (Imperial College London; Lavezzo et al.). In the general population of a high transmission area, among pregnant women admitted to a New York City hospital for birth delivery, 14% had SARS-CoV-2 without symptoms (Sutton et al.). Among people found infected in a program in Korea, 36% were asymptomatic. Then 19% started having symptoms, showing that they had actually been presymptomatic (Lee S, Kim, et al.). After several residents of a long-term care skilled nursing facility in Washington state had COVID-19, scientists tested 93% of residents, and found that about half of those infected did not show symptoms (Kimball et al.). When large numbers of cruise ship passengers and crews were tested for viral RNA, 26% – 51% of those infected were asymptomatic. When they tested the same individuals repeatedly, 17.9% of those infected never showed symptoms (Mizumoto et al.). So, much of the transmission on the cruise ships was probably from asymptomatic people (Moriarty et al.). Many children with few or no symptoms shed large numbers of coronaviruses, and so could be transmitting it to adults, who could later develop severe infections (Kelvin and Halperin; Qiu et al.; Xu Y, Li X et al.). In London care homes with no reported COVID-19 cases, an antibody seropositivity survey found they ranged from 10% – 56%, revealing silent transmission (Jeffery-Smith et al.). In Henan China early in the pandemic about 42% of infected people were asymptomatic (Li C, Zhu Y, et al.). A survey of University of Arizona students found 79.2% of infected were asymptomatic (Schmitz et al.). A review of initial epidemics in several countries found 5% – 80% of cases were asymptomatic (Heneghan, Brassey, et al.).
COVID-19 can spread more easily than many other infectious respiratory diseases, including in the incubation period and asymptomatic infections (Christakis; Ge et al.; Gandhi M, Yokoe, et al.; Joseph), or within a few days after symptom onset (Cheng HY, Jian SW “Contact Tracing”; Ge et al.). Symptoms usually start about 5 days after exposure, ranging from 2 -14 days. This virus quickly multiplies in the person, and produces millions of viruses in mucous and saliva in a few days (Huang N, Pérez, et al.). Infected people can shed viable viruses 6 days before symptom onset. After symptoms stop, viable viruses still shed from that person for up to 20 days, and viral RNA for up to 92 days, with a median of 18.4 days (Fontana et al.; Karia et al.). Patients start to develop immune antibodies in a few days after exposure, but the viruses continue multiplying and shedding, and gradually decrease later (Lauer et al.; National Academies of Sciences, “SARS-CoV-2 Viral shedding”; Tan et al.; Wiersinga et al.; Wölfel et al.; World Health Organization “Immunity…”). In that sequence of events, cases are more likely to transmit when presymptomatic than symptomatic (Li F, Li Y-Y, et al.). These processes facilitate people spreading SARS-CoV-2 through their social networks more than most infectious diseases (Christakis).
Isolation and quarantine
[Publication date of latest article cited: June 30, 2021]
Since many infected people are asymptomatic or presymptomatic, as described above, they should isolate themselves from others (Lee S, Kim, et al.). Altogether, people with COVID-19 symptoms can probably transmit to others about two days before symptoms begin, and then for about another 7-10 days. After symptoms start, SARS-Cov-2 replication probably continues for about a week in most patients (Cevik, Tate, et al.), then usually decreases so viruses could not be cultured from most patients after two weeks. But weeks later some patients might still have non-infectious RNA found by PCR (National Centre for Infectious Diseases). So, people who have been infected should isolate from other people for at least 10 days after symptoms started, and their symptoms improved, and they have not had a fever for 24 hours without using fever reducing medicines. After meeting all those conditions, they can come out from isolation (Centers for Disease Control “Duration of Isolation”; Centers for Disease Control “Symptom based strategy”; Gurley; Sethuraman, Jeremiah.).
People who have been exposed to an infected person, but do not show symptoms, should prevent transmitting to others. Called “contacts,” they should remain quarantined, avoid contaminating surfaces or coughing in rooms used by others, for 10 days if they do not develop symptoms, or for 7 days if they test negative. Or they could remain quarantined for 14 days if necessary (Centers for Disease Control “When to Quarantine”; Centers for Disease Control “Symptom based strategy”; Dwyer; Gurley; Sethuraman, Jeremiah.).
People who live with COVID-19 patients should protect themselves for weeks afterwards. When scientists followed up both ordinary COVID-19 patients (Bai et al.; Hu et al.; Xing et al.) and medical staff patients (Lan et al.), they found that most of those recovered had no SARS-CoV-2 RNA, then later started having viral RNA again. Their families living with them used infection prevention methods, but some of their family members were infected.
These patterns of symptoms, RNA, and viruses could allow many asymptomatic and presymptomatic people to continue transmitting to many others. This could permit the pandemic to continue for many months, and resurge in communities that relax social distancing, testing, and treatment (Christakis; Clipman et al.).
Contact tracing, isolation, and quarantining succeeded in reducing transmission. For example, in some fitness centers in Korea, contact tracing and social distancing stopped an outbreak (Bae, Kim, et al.). In a French hospital program in an area where many people practiced quarantining and other non-pharmaceutical interventions, during this pandemic influenza and respiratory syncytial virus cases were reduced to fractions of those in past years. Rhinovirus cases decreased among adults, and increased among children, possibly because schools remained open and children were not required to wear masks (Mansuy et al.). But large minorities of infected people and contacts did not regularly do the recommended behaviors because they did not access community support and tests, lacked control over leaving home, did not perceive benefit in following the rules, felt uncertain about their symptoms, and distrusted the Government (Eraso et al.).
[Publication date of latest article cited: September 1, 2021]
After people have COVID-19, most probably become immune, and most probably will not get infected again (Kim DS, Roland-Jones ,et al.; Lumley et al. “Antibody Status and Incidence”). For example, a study of 69% of the Danish population found that among those not infected in the first surge, 3.27% were infected in the second surge. In comparison, among those infected in the first surge, only 0.65% were infected in the second surge. This means that natural infection provides 80% protection for those aged under 65, and 47% for 65 and older (Boyton, Altmann; Hansen et al.).
The body’s humoral immune system responds soon, creating antibodies to antigen molecules on SARS-C0V-2. Many convalescent patients developed SARS-CoV-2 neutralizing antibodies, IgM, IgG, and IgA which decreased months later ( Allegra et al.; Alshamarry et al.; Choe PG, Kang, et al; Choe PG, Kim, et al.; He Z, Ren, et al.; Joseph; Kim DS, Roland-Jones, et al.; Ledford; Lei et al.; Long et al.; Lowe; Lumley et al.”Duration, dynamics and determinants of SARS-CoV-2”; Poland et al.; Reifer et al.; Ricci et al.; Rodda et al.; Seow et al.; Shu et al.; Stephens, McElrath; Tavasolian et al.; Wajnberg et al.; Wu F, Liu, et al.). Follow-up surveys of infected people found 90% had antibodies for at least four to six months (Duysburgh et al.; Figueiredo‐Campos et al.; Gudbjartsson et al.; Zhang X, Lu, et al.), and 69%-91% had antibodies after 8 months (Choe P, Kim, et al.). A longitudinal serological survey in Wuhan found that, among people with antibodies, about 40% had neutralizing antibodies during the nine months studied (He Z, Ren, et al.).
Having antibodies probably protected people from infection (Kim et al.). For a small scale example, on a fishing boat, three crew members had antibodies. During their next voyage, one other person infected most of the others, but not the three already having antibodies (Addetia et al.; Tingley). For a larger scale example, one study showed that among healthcare workers with antibodies, none developed symptomatic infection in the next 6 months (Lumley eta l. “Antibody Status and Incidence”). A study of patients for 6 – 8 months found spike IgG antibodies were stable, spike-specific memory B cells increased from 1 to 6 months, and CD4+ T cells and CD8+ declined (Dan et al.). A nation-wide follow-up of millions found that those initially having antibodies later had declining ratios of diagnostic nucleic acid amplification tests (NAAT) relative to people who initially lacked antibodies. This indirectly suggests that people with antibodies had SARS-CoV-2 at first, which disappeared, and then they did not get infected again (Harvey R, Rassen,et al.). Individuals’ immune responses varied greatly, with different amounts of IgM, IgG, IgA, and neutralizing antibodies (Nab) resulting in differing immunity (Kim DS, Roland-Jones, et al.).
Then the body’s cellular immune system responds, creating memory T cells, CD4+ helper T cells, CD8+ killer T cells, and memory B cells, which are kinds of white cell lymphocytes. They develop and provide immunity for over (Allegra et al.; Alshamarry et al.; Calhoun et al.; Grifoni et al.; Ledford “What the Immune Response”; Lewis R; Lowe; Mandavilli “Can you get COVID-19 again?”; Mateus et al.; Ni et al.; Poland et al.; Ricci et al.; Robbiani et al.; Sekine et al.; Stephens, McElrath; Tavasolian et al.; Thieme et al.; Yong “Immunology”; Zuo J et al.). Individuals’ immune responses varied greatly, with different counts of memory T cells, CD4+ T cells, CD8+ T cells, and memory B cells associated with in differing immunity (Kim DS, Roland-Jones, et al.).
Some people who probably had previous coronaviruses, such as SARS, MERS, or common colds, developed T cells which could attack SARS-CoV-2 (Le Bert et al.). Consequently, patients with no detectable antibodies might still be immune, because the T cells, B cells, and small amount of antibodies could prevent infection (Iwasaki, Medzhitov; Sette, Crotty). Altogether this shows why vaccines effectively immunize many people (Lowe). Patients’ antibodies, T cells, and B cells varied, showing why disease-induced, and vaccine-induced immunity among large populations varies (Juno et al.; Wu F, Liu, et al.). But scientists do not yet know how long immunity will last (Centers for Disease Control “Duration of Isolation” and “Updated Isolation Guidance”; Ledford “What the immune response”).
In contrast, scientists proved that some people were infected a second time with a genetically different strain of SARS-CoV-2. Most of them had more serious symptoms the first time, and less serious or no symptoms the second time. This may show that most people’s immune systems can defend them from reinfection, and that reinfections might cause mild or no symptoms in some people (Iwasaki; Mandavilli “Coronavirus reinfections”; Marchione; Regalado; To KKW, Hung, et al.; Van Elslande et al.). But, in some cases the second infection caused more serious symptoms than the first, even causing death, showing that the immune system did not protect them thoroughly (BNO News “COVID-19 reinfection tracker”; Bowen; Mulder et al.; Prado-Vivar et al.; Tillett et al.). More scientists are developing methods to test large numbers to find if they have viral relapse, continuing infections, reinfections, or inflammatory rebounds. Then they can estimate the incidence of re-infections (Gousseff et al; Ledford “Coronavirus reinfections”; Murillo-Zamora et al; Tomassini et al; Yeager). So, SARS-CoV-2 could continue circulating for years, even if people have infection-induced or vaccine-induced immunity, similar to the annual epidemics of common colds and influenza (Walker “First case”).
Some patients had COVID-19 symptoms for months, most testing positive for viral RNA, and some not (Alwan; Carfi et al.; Fontana et al.; Garner; Malta; Mandavilli “Can you get COVID-19 again?”; Marshall; Rubin; Yong “COVID-19 can last..”and “Long haulers are Redefining” and “Long Haulers are Fighting”; Witvliet). Some had symptoms and organ damage; others had symptoms without organ damage (Goldenberg). Some apparently recovered, had no symptoms or viral RNA, and then showed RNA later. Some of those also had antibodies (Katz; Liotti et al.). Some had no symptoms or viral RNA, and then showed symptoms and RNA later. They will probably need more medical treatments, and research on improving treatments and self-care. These probably were continuing the same disease case, and were not reinfected. More follow-up studies could discover if they had the same or continuing infections (The Lancet “Facing Up to Long COVID”; Yong “Immunology”). Follow-up found none transmitting to contacts (Korea Centers for Disease Control; Mandavilli “Can you get COVID-19 again?” ) and none having viruses that could infect cells (Lu J, Peng J et al.; Simon). Their long term symptoms might be caused by SARS-CoV-2 continuing to attack their bodies. Or, their immune systems could be reacting against their own internal organs, creating autoreactive antibodies or autoantibodies (Mandavilli “Some Covid Survivors”; Woodruff et al.; “Long Haulers are Fighting”). These varied disease patterns can be classified in three categories: “Acute Infection or COVID-19;” “Postacute Hyperinflammatory Illness;” and “Late Inflammatory and Virological Sequelae” (Datta et al.). These patterns are similar to other postinfectious syndromes, including myalgic encephalomyelitis, chronic fatigue syndrome, fibromyalgia, and post-treatment Lyme disease (Aucott, Rebman; “Long Haulers are Fighting”).
Doing controlled tests on humans to discover how many were infected and developed immunity would be difficult and not-very-ethical (Spinelli et al.; World Health Organization “Key Criteria”), so scientists have been experimenting on animals who get COVID-19 similarly to humans, including hamsters (Chan J, Zhang et al; Imai et al.; Sia et al.) and rhesus macaques (Chandrashekar et al; Deng, Bao et al.; Yu, Qi et al.). They found that some hamsters (Imai et al.) and rhesus macaques (Chandrashekar et al; Deng, Bao et al.) infected with COVID-19 developed antibodies and were protected against getting infected again.
These different humoral and cellular immunity responses associated with different symptoms of natural COVID-19 infection show why people’s responses to SARS-CoV-2 vaccines vary also (Kim et al.).
Biological Herd immunity
[Publication date of latest article cited: September 7, 2021]
Biological herd immunity occurs when most people develop immunity to the disease pathogen, either from natural infection or vaccination. Some experts hypothetically estimated that perhaps if 43% – 80% of a population are immune to SARS-CoV-2, then it could not transmit through the whole population (Clemente-Suárez; Hartnett; Mandavilli “Can you get COVID-19 again?”; Mandavilli “What if heard immunity”; Randolph, Barreiro).
But most surveys found much lower percentages have immunity. For example, a survey in Zambia in March – December 2020, found 10.6% positive for either rt-PCR-detected current infections or ELISA-detected infection history (Mulenga et al.). By December 2020, antibodies increased to 27.6% of blood donors in Nuevo Leon, Mexico (Martinez-Acuña et al.). A study of blood plasma collected from urgent care and routine care patients of a New York City hospital in May – July 2020 discovered that 20% of the people have antibodies, only a fraction of the number needed for herd immunity (Stadlbauer et al.). A serological survey of Wuhan found that about 7% had antibodies, after an initial epidemic, then lockdown, and strict control measures (He Z, Ren, et al.; Strugnell, Wang). A survey of US residents by address found 11.9% had antibodies (Sullivan P, Siegler, et al.). A survey of US dialysis patients’ blood samples in July 2020 found about 9% had antibodies, ranging from 3.5% in the west to 27% in the northeast (Anand et al.). A survey of routine care laboratory samples across the US in July – September 2020 found under 9% had antibodies (Bajema et al.). So, Europeans and Americans had been infected at rates only a fraction of those needed to create herd immunity (Anand et al.). A meta-analysis of 82 seroprevalence surveys world-wide through 2020 found that on the average, 8% of people had antibodies (Chen X, Chen Z, et al.; Murhekar, Clapham). A review of European COVID-19 statistics in June 2020 found that they were not near herd immunity, and that social distancing and other interventions caused the epidemics to plateau at that time (Okell et al.).
But in some populations the percentage with antibodies has come close or exceeded the estimates of the percent needed for herd immunity, and yet more people are still getting infected. This shows that herd immunity probably needs more than those percentages immune. For example, in the USA in May 2021, 83% had infection or vaccine induced antibodies (Jones JM, Stone M, et al.). In Cape Town, South Africa 40% had antibodies, ranging from 31% – 46% in sub-populations, which may have slowed but not stopped transmission (Hsiao et al.). In some US prisons 65% of inmates were infected, and hundreds died, yet the epidemic was still spreading there (Aspinwall, Neff; Lin, Christensen; Saloner et al.). This shows that herd immunity probably needs more than 65% immune. In Manaus, Brazil an estimated 76% had antibodies by October 2020 (Sabino et al.).
These survey results probably indirectly predict the effects of COVID-19 immunization programs. When 8% of a population has been immunized or is naturally immune, probably transmission in the whole population will slow little. When 40% are immunized or naturally immune, transmission will slow moderately. And when 80% are immunized or naturally immune, transmission will slow substantially. Scientists should conduct more random sample population surveys, or samples of pre-natal women, in order to monitor the destructive spread of these viruses, and to predict the constructive progress of immunizations.
Some scientists predict that the US will probably not reach herd immunity for COVID-19. Even with >80% immune from infections or vaccination, infections are still spreading in the US. Among the remaining people, many feel reluctant to get the vaccination. Many do not often access health care systems. As the viruses spread among unvaccinated people, more variant viruses will mutate, and some may resist vaccine-induced immunity. Mutating variants will continue to infect even some previously infected or vaccinated people. In a race between variants and vaccinations, the variants may continue to stay ahead (Mandavilli “Reaching ‘Herd Immunity’ Is Unlikely“). In this situation, using many prevention methods to eliminate transmission has disrupted economies and societies less than trying to mitigate and tolerate transmission and disease (Oliu-Barton et al.).
Some scientists advocated allowing healthy members of the public to live and work as they did before the pandemic, get infected, and develop natural herd immunity, while protecting more vulnerable people from infection (Kulldorff et al.) Others disagreed, saying this would cause much suffering; it is not feasible to identify, isolate, and protect large numbers of vulnerable people; and many public health measures would better protect people (Alwan, Burgess, et al.; Gronvall; Omer et al.; Spellberg et al.; The John Snow Memorandum; Walker “Researchers blast”). This debate will continue (Burki “Herd Immunity”).
This concept of natural herd immunity for COVID-19 seems to be based on three inaccurate assumptions about pathology, psychology, and immunity.
- It assumes that SARS-CoV-2 causes four conditions: symptomatic infections, asymptomatic infections, immunity, or death. But it can also cause long-term symptoms (Carfi et al.; Garner; Goldenberg; Malta; Marshall; Rubin; The Lancet “Long COVID”; Witvliet) or long-term organ damage, especially to the lungs and heart among 7.2% – 27.8% of COVID-19 patients (Abbasi; Adu-Amankwaah et al.; Goldenberg; Kim JH, Levine, et al.; Mitrani et al.; Moayed et al.; Puntmann et al.; Yancy, Fonarow).
- If governments relaxed some restrictions that would relieve some economic problems and anxieties. But people would notice others’ short and long term symptoms and organ damages, fear the consequences, and impose restrictions on each other. Many families, organizations, villages, etc. would debate and adopt widely varying rules, some science-based, others imagination-based, some stricter than government rules. Some of these would cause more economic problems and anxieties than the recent government restrictions.
- It assumes that infection results in immunity or death. But follow-up of Danish people found that natural infection had only 80% protective effect against later infection among people under 65, and 47% among those 65 and older. This implies that 20% of the younger people did not develop immunity, and 53% of the older people (Boyton, Altmann; Hansen, et al.).
- When large numbers of people have COVID-19, medical workers and organizations are overstressed, preventing them from providing the best care. So, more COVID-19 patients die than when smaller numbers of patients have COVID-19. More patients with other diseases get severely ill and die (Christakis; Goldenberg).
Social Herd Immunity
[Publication date of latest article cited: May 12, 2021]
Social herd immunity for an infectious disease occurs when most people know someone who got sickened with that disease, and talk to each other about effective prevention methods. When COVID-19 started spreading through big cities, those residents knew people who then got the disease, so people started telling others about it. In towns and rural areas, large numbers of people did not yet know anyone diseased, so some denied the seriousness of this disease or, resisted using scientifically valid COVID-19 prevention methods. As more were sickened, more started talking realistically about it, the process by which communities develop social herd immunity to a disease.
This affected people’s perceptions of the pandemic. A survey in February – March 2021, after a year of the pandemic, found that 19% of Americans know a close friend or relative who died of COVID-19. 67% worried that they or a household member will get COVID-19. 65% always wear a mask outside home near other people (AP-NORC Center). This shows that large portions of Americans are attaining social herd immunity. By mid-2020, many people felt tired of prevention methods and said the pandemic was ending when infections were actually increasing (Christakis).
Some authors used “social herd immunity” with other informative meanings.
- Williams and Cooper wrote that “The US must develop a new kind of ‘herd immunity,’ whereby resistance to the spread of poor health in the population occurs when a sufficiently high proportion of individuals, across all racial, ethnic, and social class groups, are protected from and thus ‘immune’ to negative social determinants.” This meaning is broader than the one above, because it includes many actions and ideas preventing many diseases. Disparities in this kind of social herd immunity did affect COVID-19 transmission. For example, in Washington DC, neighborhoods with higher concentrations of African Americans and low income people, there were more COVID-19 cases, and less testing than other neighborhoods (Brown K, Lewis, et al.). In California, Latinx people are more likely to live in high-exposure-risk households, are overrepresented in cumulative cases, and are underrepresented in cumulative testing. Blacks have a higher death rate, and Asians have a lower testing rate (Reitsma et al.).
- Wise, interviewing Alang, gave examples of that broad meaning, such as more upper income people working with information through the internet from home safe from COVID-19 transmission, while only small percentages of low income people can work from home. This reduces transmission in upper income neighborhoods: “Regardless of individual income, all residents of these privileged neighborhoods benefit from a kind of “social herd immunity” against the virus, while all residents of disadvantaged neighborhoods are at greater risk. Alang posed the scenario: If you shop at a grocery store where everyone is exposed because there’s an essential worker in every single house, that increases your exposure. But if you work in a neighborhood where everyone can work from home, then that reduces your exposure, she said.”
- van Schaik described mutual aid: “Communities will need to come together to provide ‘social herd immunity’ by helping those out that are in quarantine (for example, by checking in on them via social media or direct messaging apps and doing some shopping for them.”
- Robertson used social herd immunity to mean society’s understanding and support for vaccines persuades more people to get vaccinated, “that protects people who can’t be vaccinated for health reasons”.
- Some authors used “herd immunity” as a virology metaphor for other topics. For example, Park described “inclusive science communication as a vaccination tool of sorts to combat discriminatory practices and ideologies in science.“
[Date of latest publication cited: October 1, 2021]
Probably most COVID-19 transmission occurs indoors (Centers for Disease Control and Prevention “Scientific Brief: SARS-CoV-2 and Potential Airborne Transmission”; Centers for Disease Control and Prevention “Scientific Brief: SARS-CoV-2 Transmission”; Morawska L, Allen J, et al.; Wang C, Prather K, et al.[; WHO “Coronavirus disease (COVID-19): How is it transmitted?”; Xu C, Liu W, et al.). Contact tracing studies of who infected whom found many episodes in which people interacted indoors, and few with transmission outdoors (Bromage; Frieden, Lee; Furuse et al.; Leclerc et al.; Qian H, Miao, et al.). The previous sections (on asymptomatic transmission, and fomites) described patients transmitting to their families at home. In other episodes, people were breathing, coughing, sneezing, yelling, and touching each other (Asadi, Wexler, et al.; Atkinson et al.; Furuse et al.; National Academies “Airborne Transmission of SARS-CoV-2”; Tang JW, Li et al.) in restaurants (Kwon KS, Park, et al.; Li Y, Qian, et al.; Lu J, Gu et al.), a telephone call center (Park SY, Kim, et al.), choir rehearsal (Hamner et al.), indoor sports (Dawson), family gatherings (Bromage; Ghinai, Woods et al.), a meat packing plant (Guenther), restaurants and bars (Adam et al.), a nursing facility that recycled air in rooms with little outside air entering (de Man et al.), an international business conference (Lemieux et al.; Sagonowsky), fitness centers (Bae, Kim, et al.; Jang et al.), a squash court (Brlek et al.), indoor religious festivals (Antibody Everybody; Zyskind et al.), and barracks-style migrant worker dormitories (Gorny et al.). One person even infected two others up to 6.5 meters away, in only 5 minutes, along air conditioning flow (Carman; Kwon S, Park, et al.; Tufekci “Small Data”).
Close, prolonged contact indoors with presymptomatic and symptomatic cases caused several cluster outbreaks (Cevik, Bamford, Ho). The relationships most likely to transmit were:
- friends, family members (Lee E, Wada et al.; Madewell et al.; Thompson H, Mousa, et al.; van Elsland; Sabino),
- taking the same transportation, living with each other, being within 6 feet of each other, and eating together, more likely than brief contacts with non-family (Bagget et al.; Bi et al.; Burke et al.; Chen Y, Wang, et al.; Cheng HY, Jian et al.“Contact Tracing Assessment”; Danis et al.; Ghinai, McPherson et al.; Jing, Liu, et al.; Li W, Zhang et al.; Ng et al.; Yong SEF et al.).
In superspreader events, large groups talked, sang, etc. indoors. But doing those activities outdoors, or keeping quiet or speaking softly indoors (such as theaters, classrooms, or offices), did not spread COVID-19 to large numbers (Kay; Wang C, Prather K, et al.). Superspreader events have been classified as “Societal” (in which all members could potentially transmit to outsiders, and thus are difficult to control) and “isolated” (few members could transmit outside, and could be quarantined) (Majra et al.). Small numbers of people transmitting in superspreading or cluster outbreaks probably cause a disproportionate amount of transmission, called “overdispersion in transmission” (Lee E, Wada et al.)
Generally, outdoor venues are safer, indoor places with flow-through ventilation are less safe, and indoor places with little ventilation are the least safe (Khazan; Heil; Wang C, Prather K, et al.). Studies of cell phone mobility comparing US counties and census block groups found that more travel to less-essential businesses (restaurants, fitness centers, and hotels) was associated with higher transmission (Chang S, Pierson et al.; Children’s Hospital; Cooney “Restaurants and gyms”; Dockrill; Rubin et al.). More staying in residences was associated with less increases in COVID-19 incidence (Sehra et al.). A study comparing COVID-19 outpatients to other matched control-participants found that eating in restaurants was the variable most associated with infection (Fisher KA, Tenforde, et al.). US Counties allowing on-premises dining in restaurants had COVID-19 case growth rates 40 – 100 days after reopening (Guy et al.). In order to help those businesses continue financially, and gain their benefits, many people are buying their products and services safely. For example, they ate restaurant and bar food and drinks outdoors, or took it home, or exercised outside gyms, or paid for cooking, nutrition, or exercise lessons from restaurant, bar, and gym personnel.
During winter, more people will congregate indoors. Cold winter air is often lower humidity than warm summer air, and heating it further reduces humidity, enabling SARS-CoV-2 laden droplets to dry, and float longer. This could increase COVID-19 transmission. (Ahlawat et al.; Allen et al.; Bazant, Bush; Cooney “Covid-19’s wintry mix”; Department of Homeland Security “S&T’s Research”; Freedman; Mallapaty; National Academies of Science “SARS-CoV-2 survival…”; Science Daily; Wang C, Prather K, et al.; Ward et al.). The lipid envelopes of enveloped viruses (such as influenza and probably SARS-CoV-2) solidify at low temperatures, and can last longer before being inactivated. Colder temperatures and lower humidity impair the cilia (hairlike covering) and mucous clearing foreign particles from people’s airways (Hassad; Moriyama et al.) and antiviral defense and tissue repair (Allen et al.; Kudo et al.).
To reduce indoor transmission, many people have been opening windows and pumping more outside air into buildings (de Man et al.; Hernandez; Murphy; Tufekci “We Need to Talk About Ventilation”; Wang C, Prather K, et al.). Increasing indoor humidity by using humidifiers could reduce COVID-19 transmission (Ahlawat; Allen et al; Bazant, Bush; Science Daily). Some experts recommended methods for using school buildings so students and teachers can both learn and prevent COVID-19 transmission, as part of an overall healthy buildings program (Harvard TH Chan School of Public Health “For Health, Healthy Buildings”; Jones E, Young, et al.; Powell; Wang C, Prather K, et al.). Others are attempting to reduce these problems by setting up tents or plastic bubbles outside restaurants in which air flows more than indoors, and by having customers wear masks when not eating, staff clean often, and maintaining social distancing (Chiu “Dining bubbles”; Starr).
To help people understand and prevent airborne transmission risks, experts developed an online spreadsheet in which one can enter information on the characteristics of a place, and the spreadsheet will estimate numbers of people who could get infected (Jimenez). Another model estimates safe limits on “cumulative exposure time” indoors, depending on the number people, time, ventilation, room dimensions, breathing rate, respiratory activity, face-mask use, and respiratory aerosols infectiousness (Bazant; Bazant, Bush).
Airplanes, buses, and cars
[Publication date of latest article cited: September 3, 2021]
It would be not-very-ethical to experiment on whether humans can get COVID-19 infection from aerosols in enclosed spaces, such as airplanes and buses (World Health Organization “Key Criteria”). But people created several natural experiments that scientists studied. The Korean Centers for Disease Control studied whether people got infected on air flights evacuating Koreans from Italy during the epidemic there. They found that two probably previously uninfected passengers were infected during the flights. But it is uncertain if they received the SARS-CoV-2 viruses from fomites or aerosols (Bae, Shin, et al). These natural experiments show that aerosols or fomite surfaces can transmit these infections.
People transmitted on buses also. Early in the pandemic, hundreds of people traveled to an outdoor Buddhist ceremony in China. One person had just started symptoms, and traveled on a bus to and from the ceremony. The only people subsequently infected either rode the same enclosed bus with recycling air conditioning, or were close to the infected person at the ceremony (Rabin; Shen et al.). One infected person probably transmitted to several others on a bus and a minivan, mainly to people who were not wearing masks and were downwind of the internal air flow (Luo et al.).
Reviews of published, peer-reviewed reports of COVID-19 risk and transmission on airplanes showed many cases of secondary transmission occurred on flights (Blomquist et al.; Rosca et al.). Transmission occurred when few people wore masks, and few or no transmission cases occurred when almost all people wore masks (Nir-Paz et al.; Freedman, Wilder-Smith). Transmission probably occurred to several people during long waits in international airports and a flight to Ireland, when some infected people and some uninfected people wore masks and some did not. The infected people then spread COVID-19 to others across Ireland (McMahon; Murphy et al). In May – September 2020, 2,866 infected people traveled on airplanes, and transmitted to 44 people, among 1.4 billion passengers. So, the risk of transmission is about one in 1.7 million (Pang et al.).
Scientists also experimented with measuring floating aerosol particles, and falling particles deposited on surfaces in commercial passenger airplanes. They found low densities of particles in the air, probably “…due to both airframes’ high air exchange rates, downward ventilation design, and HEPA-filtered recirculation.“ They found particles on horizontal surfaces, but less on vertical surfaces (Mitchell; Silcott et al.; Wade). For these reasons, there may be less risk of getting COVID-19 in a passenger plane than in most buildings (Pombal, et al.).
Airlines and health experts experimented with methods of decreasing transmission in airplanes and airports. For example, many airlines and airports required mask wearing at all times except when eating, which employees enforce (Harvard “Aviation Public Health Initiative”; Harvard “Assessment of Risks”; United). The US Centers for Disease Control and Prevention tried screening people’s symptoms and temperatures at airports, but found this ineffective for the amount of work finding small numbers of cases (Christensen; Dollaret al.).
COVID-19 risks on airplanes, trains, buses, and taxis vary according to the air circulation, air filters, seat locations, surface cleaning, and trip time (Bushwick et al.; Harries, Martinez, et al.). In a computer aided design (CAD) of air flows in a moving car, having all the windows open created the least risk of aerosols flowing from an infected person to an uninfected person, two or three windows open on opposite sides created less safe airflows, and all windows closed created the most risky airflows (Huzar, Flynn “Study Models Airflow”; Mathai et al.).