The collection of data and limitations to respond to Covid-19 pandemic
High quality data combined with timely and appropriate analysis is required to inform the response to epidemics. When an initial localized epidemic progress to global pandemic, this need becomes a vital element to achieve coordination, preparedness, and control at global level.
Nonetheless, access to timely and sound analyses becomes difficult during emergencies for several reasons, including weaknesses of the health care systems, barriers on access to health care, limited capabilities for testing, data collection and data management or limited capacity to conduct appropriate analysis.
For example, these bottlenecks have been present in major cholera epidemics affecting Haiti or Yemen in the context of the seventh pandemic. Cholera epidemics in Haiti and Yemen have well illustrated the difficulties in obtaining an accurate picture of the true extent of mobility and mortality and its evolution as a result of barriers in accessing health care and testing, which eventually compromised the deployment of adapted public health responses (1,2,3).
In the context of the COVID-19 pandemic, many countries, including some countries that historically have shown little openness to share data, have provided access to relevant clinical and epidemiological information (4).
However, differential access to health care and laboratory testing capabilities are currently two of the major limitations to have a clearer global overview of the COVID-19 pandemic.
Most countries around the world recommended, in the last two months, to increase social distancing and limit health seeking behavior for not urgent conditions to avoid the collapse of health care systems. These measures can limit as well the access to health care among COVID-19 infected individuals, which can be further compromised among populations fearing hospital isolation or infection withing health structures.
In relation with the disparity of the testing strategies, a simple metric such as the number of tests carried out per case detected, shows large differences among countries with similar level of diseases incidence.
As for example, Germany has conducted ~15 test per case detected, while France has conducted ~4 tests per case detected (5). Insufficient testing capacity may have limited the early detection of outbreaks and therefore the timeliness of the control measures. In addition, testing and isolation of infected individuals with active shedding is an important control measure itself that can only be optimally implemented when decentralized testing capacity is in place.
Access to health care and testing capacity become even more relevant in settings where the health care and surveillance systems are limited. The main risk associated with these two limitations is possible delays in detecting the emergence of local outbreaks which could entail fatal consequences in the outbreak control capacity.
First Observations in Africa
In several areas of the world including China, Europe or the US, consolidated decreasing trends have been observed in the last weeks. On the opposite, several parts of the world, including several African countries, are seeing increases in the number of cases and deaths that require close attention and follow-up.
A relevant observation documented in several African countries is that the rise of case numbers is slower than expected based on previous trends observed in the Northern Hemisphere. For example, in most European countries or the US, the number of cases doubled every 2-3 days during the first 4 weeks of the epidemic, while in DRC, Cameroon or South Africa doubling in case takes more than 10 days (6). The lower transmission results in a peak of the epidemic that is lower in case numbers and healthcare needs and also occurs later in time. The slower dynamics therefore provides additional time to prepare and implement an adequate national response to COVID-19. This additional time if properly use should allow decreasing the health impacts, direct or indirect, of COVID-19 in the months to come.
Several factors can explain this trend, including lower number of imported cases, early adoption of control measures including social distancing and prevention of mass gatherings, limited transport infrastructure, or better preparation and resilience to face epidemics. Other factors like higher household sizes or higher intergenerational mixture could become as risk factor for spread if containment is not achieved. Further analyses are needed to consolidate them and have a better appreciation of the dynamics in Africa.
The understanding of the local epidemiology is critical to provide useful guidance to operatations. Epicentre is supporting the Ministries of Health in several countries (e.g. DRC or Cameroon) and dozens of MSF missions to collect, analyze and interpret current COVID-19 dynamics to inform the implementation of the local response.
Local analysis combined with programs that fit the local needs and consider the community perceptions constitute the way forward to minimize the social, economic and health cost of this pandemic.
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1. Luquero FJ, Rondy M, Boncy J, Munger A, Mekaoui H, Rymshaw E, Page AL, Toure B, Degail MA, Nicolas S, Grandesso F, Ginsbourger M, Polonsky J, Alberti KP, Terzian M, Olson D, Porten K, Ciglenecki I. Mortality Rates during Cholera Epidemic, Haiti, 2010-2011. Emerg Infect Dis. 2016 Mar;22(3):410-6. doi: 10.3201/eid2203.141970.
2. Page AL, Ciglenecki I, Jasmin ER, Desvignes L, Grandesso F, Polonsky J, Nicholas S, Alberti KP, Porten K, Luquero FJ. Geographic distribution and mortality risk factors during the cholera outbreak in a rural region of Haiti, 2010-2011. PLoS Negl Trop Dis. 2015 Mar 26;9(3):e0003605. doi: 10.1371/journal.pntd.0003605.
3. Camacho A, Bouhenia M, Alyusfi R, Alkohlani A, Naji MAM, de Radiguès X, Abubakar AM, Almoalmi A, Seguin C, Sagrado MJ, Poncin M, McRae M, Musoke M, Rakesh A, Porten K, Haskew C, Atkins KE, Eggo RM, Azman AS, Broekhuijsen M, Saatcioglu MA, Pezzoli L, Quilici ML, Al-Mesbahy AR, Zagaria N, Luquero FJ. Cholera epidemic in Yemen, 2016-18: an analysis of surveillance data. Lancet Glob Health. 2018 Jun;6(6):e680-e690. doi: 10.1016/S2214-109X(18)30230-4
4. Azman AS, Luquero FJ. From China: hope and lessons for COVID-19 control. Lancet Infect Dis. 2020 Apr 3. pii: S1473-3099(20)30264-4. doi: 10.1016/S1473-3099(20)30264-4.