Challenges to an effective contact tracing strategy for COVID-19 in Senegal

When the Ministry of Public Health of Senegal officially announced the first confirmed case of COVID-19 on March 2, 2020, the Health Emergency Operations Center (HEOC) immediately began its investigation to identify individuals who had been in contact with the patient, a 33-year-old French national who traveled from Paris to Dakar on February 25. A thorough investigation of the patient’s activities between February 25 and 28, including his recent travel history, helped identify 9 family members and colleagues, and 130 passengers and crew members who might have been exposed to the virus [4]. As of May 8, 2020, there had been confirmed 1492 cases, with over 140 cases yet to be epidemiologically linked to existing cases [5]. This poses the challenge of an effective contact tracing strategy to prevent a rapid spread of the virus.

The HEOC uses an operational protocol for case assessment similar to that used during the 2014 Ebola outbreak [3] to conduct contact tracing. Infected individuals are identified, interviewed and isolated for treatment; their contacts are interviewed by phone for symptoms and risk assessment, and provided with guidelines on how to self-isolate or self-quarantine in their homes. Daily monitoring of identified contacts are conducted by sanitary district medical teams to assess their clinical conditions and, if necesary, link their symptoms to testing and treatment.

The contact tracing strategy employed by the HEOC, despite its merits, suffers from crucial limitations. It is widely recognized that manual contact tracing, a form of link-tracing sampling, underestimates the size of the epidemic as people usually underreports their network of contacts. Moreover, some identified contacts might be hesitant to share their infection status within the household, or even allow medical teams into their homes in fear of stigmatization from other family members and neighbors [2]. As senegalese households size is large (22 for collective households and 9 for ordinary households [1]) and community life is strong, unreported contacts, if not identified and monitored right away, can cause a rapid spread of COVID-19.

Improving the contact tracing strategy is crucial for preventing further spread of the disease. First, medical authorities should assess a contact’s ability to follow self-isolation guidelines at home, and make sure that basic needs (food, water, sanitation and medication) are provided. Public communication is key to building trust and raising awareness around the disease, especially within affected communities, as to prevent social tensions and further stigmatization. The practicability of digital contact tracing tools, in the context of a rapid community spread, should also be assessed to reduce the burden of daily monitorings by medical teams and improve data management [6].

References

[1] ANSD. Rapport définitif RGPHAE, 2013.

[2] Ka Daye Badiane, Seydou Boubakar Sarr, Samba Cor Talla, Idrissa Ndiaye, El Hadj Mamadou Ba, Ibrahima Oumar Ndour, Cheikh Tidiane Ly, Mamadou Selly Diop, Cheikh Tacko Diack, Papa Amadou Loume, Mandiaye Diouf Mbaye, Coll-Seck Awa Marie, Bousso Abdoulaye, Seydi Moussa. Experience on the management of the first imported ebola virus disease case in Senegal. The Pan African Medical Journal, (22(Supp 1):6):193–206, 2015.

[3] Centre des Opérations d’Urgence Sanitaire. Protocoles opérationnels normalisés Ebola, 2015. http://www.cousenegal.sn/wp-content/uploads/2016/07/PON-EBOLA-ONLINE.pdf

[4] Centre des Opérations d’Urgence Sanitaire. Riposte à l’épidémie du nouveau coronavirus – Covid-19, 2020. http://www.sante.gouv.sn/sites/default/files/sitrep4mars.pdf

[5] Centre des Opérations d’Urgence Sanitaire. Riposte à l’épidémie du nouveau coronavirus – Covid-19, 2020. http://www.sante.gouv.sn/activites/sitrep-18-coronavirus-riposte-%C3%A0-l%C3%A9pid%C3%A9mie-du-nouveau-coronavirus-covid-19-s%C3%A9n%C3%A9gal-rapport

[6] Centers for Disease Prevention and Control. Digital contact tracing tools for Covid-19, 2020.

Avatar
Mamadou Yauck
Professeur Adjoint

My research interests include respondent-driven sampling, capture-recapture methods, statistical network data analysis, causal inference and computational statistics.