TY - JOUR
T1 - Mathematical model to assess the impacts of aflatoxin contamination in crops, livestock and humans
AU - Mgandu, F. A.
AU - Mirau, S.
AU - Nyerere, N.
AU - Mbega, E.
AU - Chirove, F.
N1 - Publisher Copyright:
© 2023 The Author(s)
PY - 2024/3
Y1 - 2024/3
N2 - Aflatoxin contamination poses a significant challenge in food safety and security as it affects both the health of consumers and supply chains. Due to the health impacts associated with aflatoxin contamination, countries have set standards and restrictions for importing food crops and animal feed, resulting in greater economic losses to farmers, transporters, and crop processors. This study aimed to develop a mathematical model that tracks the contamination status of crops, livestock and humans in supporting efforts to control aflatoxin. The analysis of the mathematical model shows that both aflatoxin contamination-free equilibrium (ACFE) and aflatoxin contamination-persistence equilibrium (ACPE) exist. To study the dynamics of contamination, we derived the basic aflatoxin contamination number, R0 which is analogous to the basic reproduction number in epidemiological models. When R0<1, the ACFE is globally asymptotically stable, whereas when R0>1 the ACPE is globally asymptotically stable. Partial Rank Correlation Coefficients (PRCCs) for global sensitivity analysis were calculated using Latin Hypercube Sampling (LHS) to see how sensitive and significant the parameter is on each variable. Results from numerical simulations showed that decreasing crop contamination and shading rates and increasing the death rate of aflatoxin fungi in soil by 50% can reduce the basic contamination number by above 92%. Thus, it is important to introduce control measures that target crop contamination, shading and death rates of aflatoxin fungi in soil to reduce contamination in the population. Compared to other studies in aflatoxin contamination, the current study provides a thoroughly global sensitivity analysis of parameters involved in contamination and indicated the most important ones for control strategies.
AB - Aflatoxin contamination poses a significant challenge in food safety and security as it affects both the health of consumers and supply chains. Due to the health impacts associated with aflatoxin contamination, countries have set standards and restrictions for importing food crops and animal feed, resulting in greater economic losses to farmers, transporters, and crop processors. This study aimed to develop a mathematical model that tracks the contamination status of crops, livestock and humans in supporting efforts to control aflatoxin. The analysis of the mathematical model shows that both aflatoxin contamination-free equilibrium (ACFE) and aflatoxin contamination-persistence equilibrium (ACPE) exist. To study the dynamics of contamination, we derived the basic aflatoxin contamination number, R0 which is analogous to the basic reproduction number in epidemiological models. When R0<1, the ACFE is globally asymptotically stable, whereas when R0>1 the ACPE is globally asymptotically stable. Partial Rank Correlation Coefficients (PRCCs) for global sensitivity analysis were calculated using Latin Hypercube Sampling (LHS) to see how sensitive and significant the parameter is on each variable. Results from numerical simulations showed that decreasing crop contamination and shading rates and increasing the death rate of aflatoxin fungi in soil by 50% can reduce the basic contamination number by above 92%. Thus, it is important to introduce control measures that target crop contamination, shading and death rates of aflatoxin fungi in soil to reduce contamination in the population. Compared to other studies in aflatoxin contamination, the current study provides a thoroughly global sensitivity analysis of parameters involved in contamination and indicated the most important ones for control strategies.
KW - Differential equations
KW - Global sensitivity
KW - Latin Hypercube Sampling
KW - Stability analysis
UR - http://www.scopus.com/inward/record.url?scp=85177824491&partnerID=8YFLogxK
U2 - 10.1016/j.sciaf.2023.e01980
DO - 10.1016/j.sciaf.2023.e01980
M3 - Article
AN - SCOPUS:85177824491
SN - 2468-2276
VL - 23
JO - Scientific African
JF - Scientific African
M1 - e01980
ER -