@article{fdi:010086964, title = {{COVID}-19 in {A}frica : {U}nderreporting, demographic effect, chaotic dynamics, and mitigation strategy impact}, author = {{T}henon, {N}. and {P}eyre, {M}. and {H}uc, {M}. and {T}oure, {A}. and {R}oger, {F}. and {M}angiarotti, {S}ylvain}, editor = {}, language = {{ENG}}, abstract = {{A}uthor summary{I}n this study, we show (1) that two main factors can explain the lower numbers of cases and deaths per inhabitants in {A}frica : an underestimation (by a factor 8.5) of the reported cases and deaths which directly results from the under capacities of the health systems at country level, but also a genuine effect by a factor 5.1 directly resulting from the smaller fraction of elderly people. {W}e demonstrate (2) that the dynamics of the epidemic can be approximated deterministically by few variables only. {I}ts time evolution is however highly sensitive to the initial conditions which makes it unpredictable at long term. {M}oreover, dynamics can largely vary from one country to another. {F}or one country ({G}hana), it is shown that very different epidemiological evolution can occur under strictly identical sanitary conditions. {F}inally, we reveal (3) that the impact of the control measures on the contact number is effective at short term and enabled to maintain the epidemic at a relatively low level, but it is more difficult to identify distinctly the long-term role of mitigation strategy. {T}he omicron variant is very clearly detected in the recent evolution of the epidemic. {T}he epidemic of {COVID}-19 has shown different developments in {A}frica compared to the other continents. {T}hree different approaches were used in this study to analyze this situation. {I}n the first part, basic statistics were performed to estimate the contribution of the elderly people to the total numbers of cases and deaths in comparison to the other continents; {S}imilarly, the health systems capacities were analysed to assess the level of underreporting. {I}n the second part, differential equations were reconstructed from the epidemiological time series of cases and deaths (from the {J}ohn {H}opkins {U}niversity) to analyse the dynamics of {COVID}-19 in seventeen countries. {I}n the third part, the time evolution of the contact number was reconstructed since the beginning of the outbreak to investigate the effectiveness of the mitigation strategies. {R}esults were compared to the {O}xford stringency index and to the mobility indices of the {G}oogle {C}ommunity {M}obility {R}eports.{C}ompared to {E}urope, the analyses show that the lower proportion of elderly people in {A}frica enables to explain the lower total numbers of cases and deaths by a factor of 5.1 on average (from 1.9 to 7.8). {I}t corresponds to a genuine effect. {N}evertheless, {COVID}-19 numbers are effectively largely underestimated in {A}frica by a factor of 8.5 on average (from 1.7 to 20. and more) due to the weakness of the health systems at country level. {G}eographically, the models obtained for the dynamics of cases and deaths reveal very diversified dynamics. {T}he dynamics is chaotic in many contexts, including a situation of bistability rarely observed in dynamical systems. {F}inally, the contact number directly deduced from the epidemiological observations reveals an effective role of the mitigation strategies on the short term. {O}n the long term, control measures have contributed to maintain the epidemic at a low level although the progressive release of the stringency did not produce a clear increase of the contact number. {T}he arrival of the omicron variant is clearly detected and characterised by a quick increase of interpeople contact, for most of the {A}frican countries considered in the analysis.}, keywords = {{AFRIQUE} ; {EUROPE} ; {ASIE} ; {MONDE}}, booktitle = {}, journal = {{PL}o{S} {N}eglected {T}ropical {D}iseases}, volume = {16}, numero = {9}, pages = {e0010735 [24 p.]}, ISSN = {1935-2735}, year = {2022}, DOI = {10.1371/journal.pntd.0010735}, URL = {https://www.documentation.ird.fr/hor/fdi:010086964}, }