{"doi":"10.1016/j.eclinm.2020.100412","title":"Contact tracing: Can ‘Big tech’ come to the rescue, and if so, at what cost?","abstract":"COVID-19 has resulted in a unique amalgamative failure of economics, healthcare, and society. Without an effective vaccine, the precise mechanism to resuming “normal” activity remains unknown. Public health consensus seems to align on the need to test, trace and isolate infected individuals with a stepwise repeal of lock-down measures. The infrastructure for contact-tracing, however, are woefully underdeveloped worldwide. In the US, it is estimated that 180,000 contact-tracers would be required and only 0.5% of that number currently exist [1Simmons-Duffin S.We asked all 50 states about their contact tracing capacity. Here's What We Learned. NPRApr 28, 2020. https://www.npr.org/sections/health-shots/2020/04/28/846736937/we-asked-all-50-states-about-their-contact-tracing-capacity-heres-what-we-learneGoogle Scholar]. Moreover, incumbent programs are built to trace slow moving infections and are not fit-for-purpose for this pandemic. Theoretically, Big Tech (large technology companies) can provide innovative solutions to address some of the unmet challenges of contact-tracing. These solutions may seem intuitive; however, they pose a significant risk to digital security and patient privacy. Outlined below are some of proposed methods for digital contact-tracing and the threats they pose. Broadly speaking, four categories of applications (apps) are being proposed for digital contact-tracing (Fig. 1). Technical specifications aside, they vary from one another by the degree of invasiveness in terms of privacy. The more likely contenders are based on using smartphones’ location data and Bluetooth interactions to enable contact-tracing. A critical decision for developers of contact-tracing apps is whether to publish the source code (‘open-source’) or keep it private (‘closed-source’). Closed-source software are considered a higher risk as they cannot be scrutinized for security flaws by third-parties. They have unknown privacy implications since the inner-workings of the apps will only be known to developers. Algorithms may run in the background collecting unconsented data. Open-source apps have the theoretical disadvantage of delayed deployment as the codes undergo external scrutiny. A critical decision for healthcare systems using such apps is whether to store the collected data in centralized repositories or locally at the device level. Centralized data collection in ‘trusted’ platforms comes with associated privacy concerns since governments would potentially have access to citizen's location data, the ‘social graph’ of all physical contacts, and any other data the app is able to access from the phone. The track record of data loss from centralized government agencies is also a significant concern. Worryingly, many countries including China, Russia, U.K., Norway and Vietnam are taking a closed-source approach to developing their apps and using centralized frameworks. The Pan-European Privacy-Preserving Proximity Tracing (PEPP-PT) is another closed-source initiative backed by at least seven European countries including France and Italy. The trade-off between surveillance and intrusion has always been a balancing act, especially in the post-911 era as governments desire broader access to prevent terrorism, while civil liberties groups protest overreach into private lives. Maslow's Hierarchy dictates that health comes first. Nevertheless, privacy advocates are understandably concerned about how data are tracked and stored, who has access, and what happens to it when the pandemic is over. South Korean contact-tracing laws, for example, permit the government to ascertain immigration status of infected individuals. If such laws exist in the U.S., its implications may be two-fold. First, undocumented communities may not seek healthcare. Second, it is not inconceivable, that over time the same technologies and laws could be used to track undocumented migrants. Once a precedent is set, governments seldom trackback on powers granted to them i","journal":"EClinicalMedicine","year":2020,"id":81202,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":14,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9559,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":420206,"name":"Alastair Paterson","orcid":"0000-0002-8565-3304","position":1,"is_corresponding":false},{"id":233689,"name":"Pratik Sinha","orcid":"0000-0003-3751-9079","position":0,"is_corresponding":true}],"reference_count":1,"raw_metadata":null,"created_at":"2026-07-18T21:52:34.401799Z","pmid":"32766536","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}