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Table 1 Comparison of predicted case-death counts and time-varying reproduction number (Rt)

From: Assessing the impact of non-pharmaceutical interventions (NPIs) and BCG vaccine cross-protection in the transmission dynamics of SARS-CoV-2 in eastern Africa

Country Cases Deaths ICL (Rt)1 eSIR (Rt)2 SEIR (Rt)3 RMSE4 MAE5
Ethiopia (ET) 363,714 6412 2.50 (1.9–5.95) 2.75 2.98 4.257 0.027
ET + BCG 363,714 6412 1.67 (1.53.19)    4.138 0.026
ET(40 +) + BCG 134,716 5408 5.25 (3.38.16)    3.558 0.026
Kenya (KE) 252,938 5266 3.51 (2.8–7.28) 2.70 2.51 4.652 0.033
KE + BCG 252,938 5266 5.34 (3.57.99)    31.014 0.219
KE(0–39) + BCG 159,259 821 5.18 (3.87.87)    33.642 1.449
KE(40 +) + BCG 93,679 4445 5.15 (3.27.67)    3.701 0.031
Rwanda (RW) 99,559 1322 3.53 (2.7–5.60) 3.10 2.03 0.932 0.051
RW + BCG 99,559 1322 6.32 (4.5313.34)    0.962 0.053
RW(0–39) + BCG 62,693 180 5.21 (3.58.62)    0.151 0.057
RW(40 +) + BCG 36,866 1142 5.93 (4.49.97)    0.834 0.052
  1.  1ICL (Rt) - Imperial College London (ICL) model estimates of the time-varying reproduction number (Rt). 2eSIR (Rt) - the extended susceptible-infected-removed (eSIR) compartmental model estimates of the time-varying reproduction number. 3SEIR(Rt) - susceptible-exposed-infectious-recovered (SEIR) compartmental model estimates of the time-varying reproduction number. 4RMSE measures the model (ICL) prediction accuracy against the observed data in a regression analysis. It is the Root of the Mean of the Square of Errors between the predicted and the observed COVID-19 cases and deaths. 5MAE measures the accuracy of the model fit in terms of performance in its predictions - the Mean of Absolute value of Errors between the predicted and the observed COVID-19 cases and deaths. The mean Rt values projected by the ICL model overlapped with the SEIR and eSIR models. However, the ICL model tends to overestimate Rt values while the SEIR model had less variability (Table 1) [31]