In a rigorous medRxiv* preprint paper, a group of researchers demonstrate shifts in age structure and clinical characteristics of individuals affected with coronavirus disease (COVID-19) after social and economic reopening in three US states and show how elderly individuals were less able to reduce contacts when compared to the younger ones.
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the ongoing COVID-19 pandemic, has resulted in significant morbidity and mortality – especially within the United States (US).
Accordingly, state-level re-openings that happened in spring 2020 created a perfect opportunity for the resurgence of SARS-CoV-2 transmission. During this period, one pertinent question was whether human contact and mixing patterns could increase gradually without the increase in viral transmission.
The rationale for the latter was that mixing patterns would likely be linked to better distancing, masking and hygiene practices. Moreover, there was also a question of whether the outbreak’s clinical characteristics would improve after the inceptive surge of cases.
A group of researchers, led by Dr. Nathan Wikle from the Pennsylvania State University, analyzed the age-structured case, hospitalization, and death time series from the three US states (Rhode Island, Massachusetts and Pennsylvania) which have not experienced substantial epidemic rebounds during summer 2020 in comparison to March/April levels.
Transmission-capable mixing βt (in gray and blue) and mobility changes (yellow) from March 1 to August 31. The average population mixing for March 5-15 is set to 1.0 as the pre-epidemic level of transmission-capable mixing, and all other values are reported relative to this. Gray lines show 1000 sampled posterior β-trajectories with the blue lines showing the median and 95% credible intervals. Note that there is substantial uncertainty in these estimates during the first weeks of March, as case numbers were low and reporting may not have been catching a large proportion of true cases at this time. Yellow lines show the fraction of Facebook and SafeGraph users that left home at least once per day. The correlation between populationmovement (yellow) and transmission-capable population movement (gray+blue) begins to disappear in early May in all three states.
Evaluating epidemiological patterns and clinical data streams
These researchers evaluated eleven clinical data streams outlined by the respective state health departments in a Bayesian inference framework. Basically, this is constructed on an ordinary differential equation (ODE) age-structured epidemic model that entails compartments (i.e., clinical states) for hospitalization, critical care, and mechanical ventilation.
More specifically, they have inferred parameters on clinical characteristics, surveillance and transmission patterns of the first epidemic wave that took place in Rhode Island, Massachusetts, and Pennsylvania.
Then they have delineated the patterns of constantly low transmission in the three states mentioned above through August 31, subsequently comparing them to changes in human mobility metrics and appraising changes in age structure and clinical outcomes.
Finally, they have gauged the impact of the spring epidemic on elderly populations in these three states and compared infection fatality rates to the available estimates from other parts of the US.
Shifts in age structure and clinical outcomes
“We show that population-average mixing rates dropped by more than 50% during the lockdown period in March/April and that the correlation between overall population mobility and transmission-capable mobility was broken in May as these states partially reopened”, say study authors in this medRxiv paper.
In their analysis, infection fatality rates were estimated to be higher when compared to the recently published summary studies, with the differences particularly notable in the 60-79 age group where the rates were 1.5 to 2.5 times as high.
Likewise, the researchers have demonstrated that elderly individuals were much less able to decrease contacts during the lockdown period than younger individuals, leading to the outbreak concentrating within elderly congregate settings – despite the lockdown.
Furthermore, the study has also suggested that individuals infected during the spring wave and summer interval were more likely to progress to symptomatic disease in comparison to the average person in the population.
This is actually consistent with the observation that children were the least exposed during the spring and summer months. Hence the exposed population was more prone to progress to apparent symptoms and more likely to develop severe clinical outcomes.
Posterior distributions of reporting rate (panel A) and clinical parameters (panels B to E) for Rhode Island (purple, left column), Massachusetts (orange, middle column), and Pennsylvania (green, right column). (A) Reporting parameter ρ, i.e. the fraction of symptomatic SARS-CoV-2 cases that are reported to the health system, plotted as a function of time. In Rhode Island, it was known that in March testing was not available and cases could not be confirmed; therefore a spline function was fit for ρ. This same function provided a better fit for Pennsylvania data, but not for Massachusetts data. (B) Median length of medicalfloor hospital stay was 7.5 days in RI, 11.9 days in MA, and 15.7 days in PA. This parameter was constrained to be between 11.8 and 12.8 days in MA, as without this constraint identifiability issues arose due to the lack of the ‘cumulative hospitalizations’ data stream. (C) Probabilities of dying at home for the 60-69, 70-79, and 80+ age groups; 60-69 age group was included only for RI as data were insufficient in PA and MA. These are largely reflective of the epidemics passing through nursing home populations where individuals are not counted as hospitalized if they remain in care at their congregate care facility in a severe or advanced clinical state. These probabilities are important when accounting for hospital bed capacity in forecasts. (D) Age-adjusted ICU admission probability during the lockdown period in spring 2020 (lighter color) and after the lockdown (darker color). (E) Probability of hospitalization (median and 95% CIs) for symptomatic SARS-CoV-2 infections, by age group; MA estimates are excluded as these had priors set based on estimates in RI.
How to protect the most vulnerable?
In a nutshell, statistical inference described in this paper on attack rates, underreporting and shifting age-profiles may actually provide improved guidance for real-time decision making and adequate public health messaging.
“As recent policy discussions have been diverted by the capitulation and laziness of an epidemic management approach that would encourage younger/healthier populations to become infected, we should restate that our state-level analyses indicate that older individuals are not able to fully isolate during lockdown periods”, accentuate study authors.
Basically, this means that ‘protecting the vulnerable’ strategy is unworkable, as more endangered individuals will still necessitate essential care and contact. Thus, any policy aiming to protect just the vulnerable while granting the rest of the population to move freely would almost certainly fail at preventing viral introduction.
In conclusion, as individuals in the oldest age groups are more or less unaffected by the lockdown, the best solution to protect these (but also other) vulnerable populations is to limit the spread in the general population.
medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.
Marissa Mayer shoves her iPhone toward her MacBook’s webcam until it overwhelms the screen on the Google Meet video call we are sharing.
“I admire Apple,” she declares. “They are the best at what they do. But the fact that the biggest and most successful company on Earth by some measures—and certainly the best at design, bar none—thinks that when you meet someone new, that this is an ideal interface is mind-blowing. It’s like bad nerd humor.”
What Mayer is critiquing is the New Contact feature in iOS’s Contacts app—an exceedingly generic screen with fields for you to type first and last names, phone numbers, and other information. It’s not uniquely uninspired. Actually, it’s comparable to Google’s equivalent on an Android phone—and reminiscent of nearly every other piece of software for managing contacts we’ve seen throughout the history of smartphones and PCs.
Mayer has been part of that history herself—first at Google, which was a dinky startup when she joined it in 1999 as its first female engineer. She went on to shape many of the company’s most familiar product experiences before leaving in 2012 to become Yahoo’s CEO. That gig ended five years later when the storied internet pioneer was acquired by Verizon.
Now Mayer is back in the product business—and as you may have already guessed, she thinks she has a better way to wrangle contacts. That would be Sunshine Contacts, the new iPhone app (Android is in the works) from her latest company, Sunshine. If you’ve previously heard of the largely stealthy startup, it was under the name Lumi Labs, which Mayer, its CEO, says was a placeholder all along. The app is launching as an invite-only closed beta; you can download it from the App Store and sign up for an alert when it’s ready to let you in.
Joining Mayer as cofounder and president is Enrique Muñoz Torres, whose entire career has been intertwined with hers. An MIT senior when Mayer hired him as a Google associate product manager in 2004, he left that company in 2013 to join her at Yahoo, where he eventually led the advertising and search businesses. Though both Mayer and Muñoz Torres have copious experience creating and ramping up successful products, they are first-time founders. Their company currently has about 20 employees, making it the same size as Google was when Mayer joined it.
Contact management may not sound like an idea with the potential to become the next Google or Yahoo. That’s because Sunshine Contacts is just the first app in what Sunshine’s cofounders envision as a large portfolio of offerings. “From the get-go, we’re thinking about a strategy and a product line that, if executed correctly, we believe should lead to us scaling beyond a relatively trivial number of users,” says Muñoz Torres. “And over time, really having an impact at the scale that we’ve seen in previous places.”
So what is Sunshine’s bigger strategy? For now, Mayer and Muñoz Torres are sharing only so many details. Mayer describes the company’s mission as involving “group communication, event planning and organization, family sharing, and scheduling. Those are the types of everyday tasks that seem to get in the way of your relationships. Those are the types of things that we’re excited about.” It’s tough to manage your relationships if you don’t even have a well-organized means of reaching people, which is why they tackled contacts first.
“What really captured my imagination was speaking with Enrique and Marissa about using this as a foundation to build lots of services on top of the contacts and use it as a way to really better communicate with the people who matter in our lives,” says venture capitalist and Nextdoor cofounder Sarah Leary, who invested in Sunshine on behalf of Unusual Ventures. “That’s a really big idea. It’s a messy problem. It’s one that I think people have overlooked for decades.”
It’s not that nobody has ever tried to reimagine contacts as we know them. “In our journey, I feel like I’ve become a historian of contacts in Silicon Valley,” says Mayer, reminding me of some moments I’d forgotten about. Eighteen years ago, there was Plaxo, a contacts-based proto-social network started by Napster cofounder (and later Facebook president) Sean Parker. Bump, an early iPhone App Store hit, made it easy to share contact info with nearby people. Mayer also gives credit to Microsoft for work it did on contacts in this century’s first decade.
With all of those efforts having receded well into the past, there was plenty left for Sunshine to do. More than ever, in fact: Our still-accelerating reliance on an array of communications tools is only making us more dependent on contacts. But unless you’ve tended to yours far more attentively than most people, they’re probably a disaster zone—or, more likely, several of them.
“Typically, contacts are littered in a few different places,” says Rohit Chandra, Sunshine’s VP of engineering (and a former colleague of Mayer and Muñoz Torres at Yahoo). “They’ll be in your iPhone. They’ll be in your email, and maybe Google contacts. And with some of them, the information would just be sitting in an email that somebody may have sent to you. If I’m trying to reach out to somebody, it becomes my job to figure out where the latest information is and what’s accurate. It’s a headache that all of us have.”
If someone’s current, complete information is actually within easy reach, it can feel like a little miracle. Sunshine Contacts’ aim is to make it an everyday reality. And its approach follows the model set by Google’s search engine back when Mayer was one of the people figuring out how it should work. On the surface, there’s an approachable, streamlined interface. Beneath that, AI and other forms of computer science are working hard to find and organize vast amounts of information.
“A majority of the magic happens on the back end, and that’s because we curate a lot of information from a lot of different sources,” says software engineer Ankit Jain, who invited Mayer to talk about Lumi Labs at a meeting of former Google employees and was so swayed by her presentation that he ended up joining the company. Those sources start with your Apple contacts. Optionally, they can also include one or more Gmail accounts—not just the contacts therein, but also data that Sunshine can divine from content such as email signatures. Publicly available information such as LinkedIn profiles is also part of the mix, as are details that other Sunshine users enter about themselves.
Sunshine’s app aggregates all of the above, de-dupes it, and attempts to identify outdated info. It also writes it back to Apple’s contacts so that it’s available in the Phone app, Mail, and other products that hook into the default contact repository, such as WhatsApp. (Sunshine Contacts can’t dislodge Apple’s Contacts as an iPhone’s standard contacts experience, a fact that Mayer and Muñoz Torres understand and say they’re okay with.)
I gave Sunshine Contacts a try with my own contacts, which are splayed across my iPhone and two Gmail accounts, include some records so musty that I probably entered them on a PalmPilot, and even contain multiple outdated records for myself. The app ingested 23,148 entries in total and whittled that down to 13,473 by removing duplicates. It also informed me that it had been able to “enhance” 6,869 of my contacts with better information—a percentage that could theoretically balloon over time if Sunshine attracts a critical mass of users and they update their own entries.
The process is not perfect. For instance, Sunshine conflated an ex-Googler I know with a current Googler who happens to share his name. It also concluded that the correct mailing address it found for one of my colleagues was obsolete, perhaps because he lives in Cincinnati, nowhere near any Fast Company office. (In some cases, the app will seek your help—for instance, asking if two contacts are the same person or confirming that an email address it’s found is yours.)
The risk of Sunshine leaping to wrongheaded conclusions is an artifact of its own ambition. It’s applying machine learning and other technologies to challenges such as “understanding that Julia Sherman from a few years ago is the same person as Julia Hudson,” says software engineer Hemanth Sunkara. “That’s valuable information. Those kinds of insights are missing in the products out there today.”
Even if you end up undoing some of Sunshine’s would-be enhancements, your contacts should end up in much better shape than they started. And once the app has tidied them up, you can interact with them in ways that go beyond searching or skimming through an A-Z list. You can share your own contact info with someone in your database—personal details, professional ones, both, or just one item such as your cell number. You can select people and introduce them, sharing their contact information in the process. And you can use the app to ping people in your contacts and request that they update their info—one at a time, so that it doesn’t devolve into LinkedIn-like spam.
If you happen to be in close physical proximity to another Sunshine user, the app also lets the two of you quickly exchange info—a feature that Mayer acknowledges will be much handier once life returns to a semblance of normalcy.
We are not going to be targeting advertising, selling the data, doing anything of that nature.”
As with anything that involves collecting and distributing personal information about individuals, the app has its privacy implications. It’s not a white pages that lets you search for people who aren’t already in your contacts: “If I were like, ‘Hey, can I go find out Brad Pitt’s phone number on Sunshine?’, as much as I might want it, I can’t—I have no connection with Brad,” says Mayer. Nor is it a full-blown social network, since the only data it stores are various types of contact information, professional affiliations, and portrait photos. (Oh, and birthdays.)
However, the app does share facts you’ve entered about yourself with other Sunshine users who have you in their contacts. “We view that as a feature and a benefit,” says Mayer. But she acknowledges that there are instances when you might want to hide your details from a certain individual, perhaps for reasons of personal safety. When you update your info, the app shows you a list of the users who will see it. It then lets you uncheck any of them and waits 24 hours before distributing it to everybody else.
Given Mayer and Muñoz Torres’s backgrounds at Google and Yahoo—two companies whose revenue derives mostly from putting advertising in front of eyeballs—you might also wonder if Sunshine’s long-term plan is to turn its users into the product. They say that’s not in the cards. “We are not going to be targeting advertising, selling the data, doing anything of that nature,” stresses Muñoz Torres. “Those are not business models that we believe are compatible with what we’re doing.”
For now, as Sunshine focuses on scaling up its user base, its contacts app is free. The company expects that it will eventually adopt a freemium business model in which some features carry a fee.
Back to basics
In some alternate universe, Sunshine Contacts may well be a Yahoo product. Its roots are in conversations that Mayer and Muñoz Torres had at that company in 2017, when they began tossing around concepts relating to helping people with groups and events. “At that point, the company had already been sold to Verizon,” explains Mayer. “And so we said, ‘Look, this isn’t the right time or the right place.’” So they put the matter aside.
After the pair left Yahoo and spent a few months decompressing, the ideas they’d contemplated still seemed promising, so they decided to turn them into a startup. That became the company initially known as Lumi Labs, which they self-funded. (They have since lined up $20 million in venture capital from Felicis Ventures, Unusual Ventures, WIN Ventures, and angel investors, among other sources.)
For Mayer, tackling a big ambition at a tiny company is a throwback to her earliest days at Google. She even leaned into the parallels by renting office space at 165 University Ave. in downtown Palo Alto, the same address that Google called home when she joined it. “It has these funny tiled steps you walk up, and for some reason, that’s always indelibly in my mind,” she says. “So when I walk up those steps, I have that feeling of returning to that moment in 1999 when we spent the summer in that office.” (For most of this year, of course, Mayer and her coworkers have worked from home.)
The name “Sunshine” also bridges the present with Mayer’s Google past. When Craig Silverstein, Google’s first employee, asked her to choose a name for her Linux workstation, she blurted out “Sunshine,” based on the fact that it happened to be a nice day. A couple of decades later, the same word gave off the upbeat, enlightening vibe that Mayer and Muñoz Torres wanted their brand to convey. They even managed to snag Sunshine.com for their web presence and @Sunshine on Twitter.
When Yahoo ended its run as an independent company, it had about 8,600 employees. Sunshine, née Lumi Labs, started with only its cofounders. As with all fledgling companies, Mayer and Muñoz Torres’s work has been inherently hands on, sometimes in the most literal sense. “You can go from a very high-level discussion on what your strategy and product line should be to building a desk and running a wire to get the internet to work,” says Muñoz Torres.
You also hire people—and, along the way, build a culture. According to Mayer, the atmosphere they’re trying to create is summed up by the sentiment stitched on a pillow given to her by Maureen Taylor, an executive coach she worked with at Yahoo: BE NICE OR LEAVE. “If we’re going to do this, we want to do something that we’re inspired by and excited about every day,” she says. “And we want to work with people that we’re really excited to work with.”
“Every day, we have a stand-up, and any given time, somebody will raise their hand and say, ‘You know, I’m stuck,’” says program manager Annie Luu, who worked with Mayer and Muñoz Torres at Yahoo and left Square last month to rejoin them at Sunshine. “And five people will raise their hands and be like, ‘After this call, let me help you. What can I do to help?’ Mind you, five people is 25% of the company. Marissa and Enrique have really made a concerted effort to hire really nice people so that it shines through in our product.”
It’s not hard to detect similarities between the app and products in Mayer’s past.
Creating products is once again at the forefront of Mayer’s responsibilities—a welcome change from the later part of her tenure as Yahoo CEO, which was increasingly devoted to the corporate machinations that resulted in the company spinning off its investment in Chinese ecommerce giant Alibaba and selling itself to Verizon. The distance between Mayer’s brain and the Sunshine Contacts experience is short: “She likes to bring happy, bright things to life,” says investor Leary. “You see that in the products that she builds, in the way she goes about her life, the way she dresses.”
Mayer collaborates on Sunshine Contacts’ look and feel with designer Zaianne Sparrow, whose studies and career took her from her native Malaysia to Australia and then to New York and Chicago before she headed to Silicon Valley and Sunshine. “My personal style has always been very minimalistic,” says Sparrow. “And it’s great to work with Marissa, who is also very minimalistic. But the only difference is that she loves color.”
It’s not hard to detect similarities between the app and products in Mayer’s past. Its home screen features the Sunshine logo—which is, naturally, colorful—sitting atop a search field and looking a little like the Google home page that she once presided over. And the effort to impose simplicity on a potentially nebulous design challenge is tangible. Early prototypes stuffed functionality into a lengthy menu of options. Later, Mayer and Sparrow ditched the menu in favor of oversize buttons leading to key features, making the experience feel a little less like an app and a little more like a dashboard.
One thing Sunshine Contacts is not is over-tested. At Google, Mayer was famous—though not universally admired—for using A/B testing of users to inform product design. Today, she pushes back on that reputation (“everyone will have a different take on those stories”) and says that it began as a directive from above, intended to help the company avoid becoming mired in competing opinions.
Moreover, you can only let data guide the way once you already have a sizable contingent of users whose behavior you can study. To date, very few people have seen Sunshine’s app, let alone begun using it daily. “A lot of the rigorous, very experiment-driven work that I’ve done doesn’t translate here,” says Mayer.
Which is not to say that the company isn’t looking forward to throwing its app’s doors open, letting in the masses, and keeping tabs on their reactions. “We’ve done user studies, we’ve had conversations, we’ve had product brainstormings,” says Muñoz Torres. “We’ve done all the things that you do when you, when you start a new idea and you start building on it . . . but the real learning comes when you put something out there and you have more than a handful of users using it and giving you feedback, positive and negative.”
Even though Sunshine wants to stop being a one-product company as soon as possible—Mayer believes that many startups wait too long to branch out—everything to come will build on its first launch. “It’s both exhilarating and terrifying,” she says. “Because, obviously, I like a lot of the decisions that we’ve made on the product, but I’m also a seasoned enough product person to know that on the outside, no one’s going to like every decision. And there may be people who don’t even like most decisions.” If you give contacts in their current form any thought, it’s painfully clear that they’re broken. All that’s left is for the world to decide if Sunshine has fixed them.
The coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has compelled people worldwide to quarantine. To mitigate the transmission of SARS-CoV-2, countries and workplaces have been under varying stages of lockdown since the detection of the infection in December 2019 in Wuhan, China.
In mid-April 2020, it was observed that 62% of employed adults were working remotely in response to the COVID-19 pandemic. This scenario is continuing, and there is no standardized multi-site social contact study conducted in workplace settings. A study of this order helps plan strategies to address the pandemic situation – before onset as well as during.
16% of influenza transmission is estimated to occur in the workplace setting due to social interactions and respiratory infection transmissions. Likewise, the conditions at the workplace determine the SARS-CoV-2 transmission percentage.
Any significant impact of remote work on COVID-19 needs to be evaluated; this can be achieved by assessing changes in social contact patterns. In this context, Moses C. Kiti et al. published a recent medRxiv* preprint paper studying social contact patterns. In this study, they characterized the mixing across workplace environments, including on-site or when teleworking.
The median number of contacts per person per day was found to be two contacts per respondent. The authors stratified this information by day of data collection, age, sex, race, and ethnicity. This information can be broadly employed in pandemic preparedness policy for similar settings.
This study involved two multinational consulting companies ((N1=275, N2=3000) and one university administrative department ((N3=560), located in Atlanta, Georgia, USA, from April to June 2020, when the shelter-in-place orders were in effect. The employees opted into the study by accepting an email invitation. Remote working was defined as any working location (home or public space) outside their designated workplace. Employees approached were 3,835, out of which 357 (9.3%) responded on the first day of contact, and 304 completed both days of contact. The results are summarized from those respondents who completed the dairy on both days.
This study was a cross-sectional non-probability survey that used standardized social contact diaries into which the respondents were to fill in. The respondents recorded their physical and non-physical contacts over two days, documented at the end of each day.
Panel (A) shows the distribution of contacts by attributes: duration (in minutes (mins) or hours (hr)). Types of contact were conversation with physical touch (Conv & Phys), physical only (Phys), or non-physical/conversation only (Conv only). A contact was repeated if observed on both days or unique if observed on only one day. Panel (B) shows the age-stratified average number of contacts over two study days. The gray area on the x-axis indicates that all respondents were over the age of 19, however they were able to report contacts under the age of 19 years. Data shown in the graphs are for 1,548 contacts recorded by 304 participants over 608 diary-days
A median of 2 contacts per respondent on both day one and two were observed.
Most of the contacts (55%) involved conversation only – occurred at home (64%) and cumulatively lasted more than 4 hours (38%). Most contacts were repeated and within the same age groups. Participants aged 30-59 years, however, reported inter-generational mixing with children.
This study compares to similar reports from the UK and China, effective during the shelter-in-place orders in the pandemic. Pre-pandemic data is unavailable for direct comparison. While the median contact number is 2, many of the contacts were repeated, which may limit the spread of infection.
Mathematical models are used to forecast and simulate the effects of interventions implemented during pandemics. These models are highly sensitive to assumptions about how people acquire infection and how they transmit it to others.
The data on the social contact patterns – the frequency and nature of contacts that individuals make daily – determine these assumptions. The authors discuss a few selection and information biases that may be present in this study.
The authors propose similar studies to assess the changes in contact patterns to parameterize mathematical models describing disease transmission and post-lockdown due to the COVID-19 pandemic. Such studies help reduce the transmission risks, investigate prevention methods, and mitigate infection in the workplace.
medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.
Social contact patterns among employees in 3 U.S. companies during early phases of the COVID-19 pandemic, April to June 2020. Moses Chapa Kiti, Obianuju G Aguolu, Carol Liu, Ana Mesa Restrepo, Rachel Regina, Kathryn Willebrand, Chandra Couzens, Tilman Bartelsmeyer, Kristin Nicole Bratton, Samuel M Jenness, Steven Riley, Alessia Melegaro, Faruque Ahmed, Fauzia Malik, Ben Lopman, Saad B Omer medRxiv 2020.10.14.20212423; doi: https://doi.org/10.1101/2020.10.14.20212423, https://www.medrxiv.org/content/10.1101/2020.10.14.20212423v1
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Authorities have sent Victorians in self-quarantine text messages mistakenly saying they were free to leave isolation before their 14-day period ended.
The Department of Health and Human Services was unaware on Sunday night of how many people had received the wrong advice as a result of a “data entry error”.
The messages, sent on Sunday morning, told some Victorians in strict two-week isolation they were “no longer in quarantine”, several days ahead of their actual end date.
It included one Melbourne woman who was in self-quarantine with her daughter after her partner tested positive to coronavirus only on Wednesday.
The woman, who did not want to be identified, said she had been repeatedly contacted by DHHS workers via phone calls, text messages and emails during their isolation period, reminding her to adhere to the strict quarantine rules.
One such email came on Sunday morning, but just 20 minutes later she received a text saying unless she was awaiting test results or had been re-exposed, she was no longer in quarantine.
“Straight away I thought, this is a mistake, something has gone wrong here,” she said.
Her daughter did not receive the misfired text.
The woman called the DHHS hotline and was told some messages had been sent in error and to ignore the latest message and instead follow the original advice to stay home.
A DHHS spokesman apologised for the error.
“It is as simple as a data entry error that was totally inadvertent,” the spokesman said. “We’re sending out multiple messages every day to different groups who are in different stages of quarantine.
“We’re talking about thousands of messages a day.”
Asked if they would be issuing new texts to clarify the advice, the spokesman said first they would have to identify the affected group.
“That’s a mammoth task,” the spokesman said, adding if people were concerned they had received an advice messages in error they should contact DHHS.
A government spokeswoman said on Sunday night that Victoria’s contact tracing team sent about 7000 message each day to COVID-19 positive cases and their close contacts.
“The Department of Health and Human Services has advised this was an inadvertent data entry error,” she said.
Close contacts of confirmed COVID-19 cases must quarantine at home for 14 days after their last contact with the infected person.
“The COVID-19 app is not working as we hoped it would because too few people have downloaded it,” Queensland Health Minister Steven Miles told the network.
According to the Federal Government, 40 per cent of the Australian population needs to download COVIDSafe in order for it to be effective.
On June 11 the ABC reported that 6.2 million Australians had downloaded the app.
Many Australians have been reluctant to, citing privacy concerns.
The effectiveness of phone tracing apps has also been downplayed overseas, with British Prime Minister Boris Johnson saying that “no country currently has a functioning track and trace app” after failures launching a system he claimed would be “world-beating”.
However coronavirus-tracing apps have had been success in other countries, with 900,000 people notified and told to self-isolate by India‘s version last month.
The Indian app Aarogya Setu, launched on April 2, has been downloaded 131 million times, the BBC reports.
But the Herald Sun’s Jon Ralph confirmed that there was the possibility that it was a “false positive” with McKenna getting more testing, although it wouldn’t stop a 14-day quarantine.
McKenna, who returned from his native Ireland last month, and was reported to have attended a five open house viewings along with visiting friends and family despite strict AFL guidelines being in place.
McKenna’s family in Northern Ireland spoke to NewsCorp and said there were no problems for the family.
“We’re all fine, Conor is healthy, he got nothing from here,” his father Pat said.
“There’s nothing going around here, Conor’s fine and healthy and well.”
He also revealed that he was living with his brother and brother’s girlfriend while in the country.
The players are expected to come from McKenna’s training group, which includes Adam Saad, Cale Hooker, Michael Hurley, Matt Guelfi, Jordan Ridley and Mason Redman.
With so much up in the air, Brownlow Medallist and Fox Footy analyst Gerard Healy told On the Couch he thought it was “ridiculous” to have the Bombers’ first-choice defender all training together in these uncertain times.
“The reason the advice was given was for the very reason that happened on the weekend. If one of your guys goes down, then you lose the group,” he said on Fox Footy’s On the Couch.
St Kilda great Nick Riewoldt responded: “You’ve got to weigh up the risk and the reward.
“The reward, if you’re able to keep them together, might be minimal. But if it goes pear-shaped like it has, it could be catastrophic.”
More than 31,000 close contacts of people with coronavirus were identified during the first week of the test and trace system in England, figures show.
Of those, 85% were reached and asked to self-isolate for 14 days.
This was from 8,000 people testing positive for the virus. Two thirds of them gave details of close contacts.
Health Secretary Matt Hancock said it was the public’s “civic duty” to follow instructions given by contact tracers.
Speaking at the daily coronavirus briefing, he added he was not ruling out enforcement measures to make people self-isolate for 14 days if asked to do so.
About 25,000 contact tracers were recruited in England and started work at the end of May.
The NHS figures, which cover 28 May to 3 June, are the first to be released showing the progress of the contact tracing scheme.
‘Protect your loved ones’
Baroness Dido Harding, who runs NHS Test and Trace in England, said the system was working well but it “can, needs to and will get better”.
The system has been unable to reach 15% of close contacts identified – 4,809 people – either because they were unavailable, their contact details were wrong or they did not respond to texts, emails or calls from contact tracers.
Appearing alongside Mr Hancock at the briefing, Baroness Harding said that did not necessarily mean those people had not self-isolated, adding: “Only a small minority don’t want to self isolate and we need to understand why this is and what we can do to support them to stay at home.”
She said earlier there had been “good numbers of compliance” with 26,985 contacts of positive cases identified, reached and asked to self-isolate.
One contact tracer, Josie, has been working from her home in Redcar, North Yorkshire, to trace contacts.
“Everybody that I’ve spoke to has been more than happy to share the information that we need,” she told the BBC.
Baroness Harding added the “number one thing” that would improve the programme was more people getting tested for the virus once they develop symptoms.
Appealing to people to comply with the measures, Mr Hancock said: “Please do it to protect your loved ones, do it to protect your community, do it to protect the nation and do it to protect the NHS.”
In response to a question about potential enforcement to make more people co-operate with the scheme, Mr Hancock said: “We’re not ruling it out, but we don’t think we need it at the moment.”
He said the “best way forward” was to see an increase in the number of people being contacted.
Contact tracers are told to try to contact people 10 times in a 24-hour period.
Most of the people called in the first week were identified by local public health teams as part of investigations into outbreaks.
As lockdown eases, and people start to return to work and go out to shops, it is expected the number of contacts people have will start to grow from a low starting point.
In the first week of the test and trace scheme, contact was made with 5,407 people who tested positive for coronavirus, asking them to provide details of recent contacts. Their cases may also have been investigated as part of a local outbreak.
Some 2,710 with positive tests were not reached, either because their contact details were not correct or they decided not to give out information about their contacts.
A good start?
The data from the test and trace system in England has been eagerly anticipated – after all, this system will be crucial in helping contain local outbreaks, enabling the country to ease out of lockdown.
It is still early days, but how should we interpret these findings?
Firstly, the system seems to be pretty good at reaching the contacts of people who have tested positive, if those positive cases engage with the contact tracers and provide details in the first place.
The problem is a third of people who test positive are not providing details.
This could be because the contact tracers are not as good as they should be at tracking those who do not engage with the online forms (the first point of call for the system).
There have been suggestions that sufficient translation support is not always available, for example.
But incorrect contact details being provided and people simply refusing to take calls – despite repeated attempts – are certainly factors too.
The key to the success of the system will be both an efficient service and public engagement in taking calls and following the advice to self-isolate.
What is test and trace?
It’s a way of controlling the spread of the virus by asking people who have tested positive for coronavirus to share information on who they have been in close contact with.
The NHS‘ flagship test and trace system tracked down less than half of positive patients’ ‘contacts’ in the first three days of its launch, figures suggested last night.
A leaked report claimed that virus sufferers had provided details of 4,634 people they might have infected, of whom just 1,749 were texted or emailed.
The Department of Health pointed out that the figures were four days out of date, insisting the majority of contacts had since been alerted. But the document obtained by Channel 4 News comes amid concerns that many of those employed by the scheme have had nothing to do.
The NHS’ flagship test and trace system tracked down less than half of positive patients’ ‘contacts’ in the first three days of its launch, figures suggested last night (File image of NHS tracing app)
Test and trace was launched by Health Secretary Matt Hancock last Thursday. He hailed it as a ‘new way of life’ that would enable the country to come out of lockdown.
Anyone with virus symptoms is urged to order a test and if the results are positive, they are asked for the mobile phone numbers or email addresses of their recent contacts.
This includes people with whom they had spent at least 15 minutes at a distance of less than two metres – in the two days before the symptoms began and five days after.
A government diagram explained how the NHS Test and Trace system works
These contacts are then texted or emailed and asked to self-isolate for up to 14 days.
Yesterday the Government launched a major information campaign on the scheme with TV, radio and online adverts.
And on Monday, Mr Hancock claimed the system was ‘working well’, although he repeatedly refused to provide figures for the number of people who had been traced.
But Baroness Harding, who is leading the programme, reportedly told MPs last week she did not expect the system to be properly up and running until the end of this month due to likely teething problems.
The Government is hoping to publish up-to-date figures this week, then weekly updates thereafter, once it has confidence in the data.
Department of Health officials stressed that many patients with the virus were not suitable for contact tracing because they were in hospitals or care homes.
Up to 25,000 contact tracers have been hired alongside 3,000 clinical case workers. They earn between £10 and £27 an hour, depending on their expertise.
But three contact tracers told the Mail earlier this week that they had not made a single call. Another claimed she had spent much of her time reupholstering a chair because she had so little to do.
Hancock under fire over his figures
Matt Hancock has become embroiled in a public row with the country’s top statistician over testing figures.
Sir David Norgrove accused the Government of misleading the public with its daily testing figures, saying they are ‘still far from complete and comprehensible’.
Matt Hancock has become embroiled in a public row with the country’s top statistician over testing figures
It is the second time the UK Statistics Authority chairman has hit out at the way Covid-19 tests are being presented. Sir David said it was ‘not surprising’ the data had been ‘widely criticised and often mistrusted’. Health Secretary Mr Hancock responded by saying he would publish details of how the 200,000 tests would be counted.
The Government has hit targets to have the capacity for 200,000 tests by the end of May. But in a letter to No 10, Sir David said: ‘The aim seems to be to show the largest possible number of tests, even at the expense of understanding.’
A Department of Health spokesman said: ‘Our approach throughout has been to increase transparency.’
On Monday it was revealed scores of the 25,000 employees hired by the Government had come forward to say they have had no positive cases allocated to them since the launch, with one even suggesting there was a fault with the system.
Contact tracers say the system remains ‘shambolic’ and unfit for purpose as millions of pupils return to school today. Workers last week also complained they hadn’t had any training by the time it launched and had waited weeks for log-in details.
Details of those who test positive are passed to a company called Sitel, which is running the track and trace handling across the UK.
Agents read from a prepared script when they are given the name and telephone number of a person who has been diagnosed with Covid-19.
They ask for the details of friends and family the infected person has come into contact with during the previous two weeks.
The tracing agent then makes contact with those on their list and informs them they have to self-isolate.
One tracer said colleagues who were on shift were ‘sitting there all day waiting and just refreshing their screens’. He said: ‘They’ve got nothing to do.’
One of the 3,000 clinical case workers hired by Public Health England said she had completed three four-hour shifts, at £27-an-hour, but hadn’t made any calls yet. She told The Times: ‘I have had absolutely nothing to do.’
The nurse said she had seen ‘zero cases’ on the system throughout three shifts and felt ‘tremendously guilty about doing the shifts and being paid and not having anything to do really’.
‘It’s very obviously not ready,’ she said. ‘Something is not working between CTAS and the test results that are coming in.’
A Department of Health spokesman said: ‘These figures are outdated and fail to reflect the huge amount of work already under way, with thousands of people already contacted in just a matter of days and their contacts successfully traced.
‘We are working with the UK Statistics Authority to finalise the most useful information to publish on its performance and will be providing weekly updates shortly.’