It is proposed to monitor spatial and temporal spreads of epidemics via solution of a Coefficient Inverse Problem for a system of three coupled nonlinear parabolic equations. A version of the second generation of the convexification numerical method is developed for this problem. On each iteration, a linear problem with the incomplete lateral Cauchy data is solved by the weighted Quasi-Reversibility Method, where the weight is the Carleman Weight Function (CWF). This is the function, which is involved as the weight in the Carleman estimate for the corresponding parabolic operator. Convergence analysis ensures the global convergence of this procedure. Numerical results demonstrate an accurate performance of this technique for noisy data.

翻译：本文提出通过求解一个由三个耦合非线性抛物型方程组成的系统的系数反问题来监测流行病的时空传播。针对该问题，开发了第二代凸化数值方法的一个版本。在每次迭代中，通过加权拟可逆性方法求解一个具有不完整侧边柯西数据的线性问题，其中权重为卡尔曼权重函数。该函数是作为相应抛物型算子的卡尔曼估计中的权重引入的。收敛性分析确保了该过程的全局收敛性。数值结果表明，该方法在噪声数据下具有准确的性能。