TY - JOUR
T1 - Are predictions of bovine tuberculosis-infected herds unbiased and precise?
AU - Hone, Jim
N1 - Funding Information:
The author acknowledges the support of the Institute for Applied Ecology, Jason Weber, and the University of Canberra.
Publisher Copyright:
© The Author(s), 2023.
PY - 2023/9/20
Y1 - 2023/9/20
N2 - Bovine tuberculosis (bTB) is prevalent among livestock and wildlife in many countries including New Zealand (NZ), a country which aims to eradicate bTB by 2055. This study evaluates predictions related to the numbers of livestock herds with bTB in NZ from 2012 to 2021 inclusive using both statistical and mechanistic (causal) modelling. Additionally, this study made predictions for the numbers of infected herds between 2022 and 2059. This study introduces a new graphical method representing the causal criteria of strength of association, such as R
2, and the consistency of predictions, such as mean squared error. Mechanistic modelling predictions were, on average, more frequently (3 of 4) unbiased than statistical modelling predictions (1 of 4). Additionally, power model predictions were, on average, more frequently (3 of 4) unbiased than exponential model predictions (1 of 4). The mechanistic power model, along with annual updating, had the highest R
2 and the lowest mean squared error of predictions. It also exhibited the closest approximation to unbiased predictions. Notably, significantly biased predictions were all underestimates. Based on the mechanistic power model, the biological eradication of bTB from New Zealand is predicted to occur after 2055. Disease eradication planning will benefit from annual updating of future predictions.
AB - Bovine tuberculosis (bTB) is prevalent among livestock and wildlife in many countries including New Zealand (NZ), a country which aims to eradicate bTB by 2055. This study evaluates predictions related to the numbers of livestock herds with bTB in NZ from 2012 to 2021 inclusive using both statistical and mechanistic (causal) modelling. Additionally, this study made predictions for the numbers of infected herds between 2022 and 2059. This study introduces a new graphical method representing the causal criteria of strength of association, such as R
2, and the consistency of predictions, such as mean squared error. Mechanistic modelling predictions were, on average, more frequently (3 of 4) unbiased than statistical modelling predictions (1 of 4). Additionally, power model predictions were, on average, more frequently (3 of 4) unbiased than exponential model predictions (1 of 4). The mechanistic power model, along with annual updating, had the highest R
2 and the lowest mean squared error of predictions. It also exhibited the closest approximation to unbiased predictions. Notably, significantly biased predictions were all underestimates. Based on the mechanistic power model, the biological eradication of bTB from New Zealand is predicted to occur after 2055. Disease eradication planning will benefit from annual updating of future predictions.
KW - causality
KW - disease control.
KW - wildlife population control
KW - brushtail possum
KW - Bovine tuberculosis
KW - bovine tuberculosis
KW - bias
KW - precision
KW - prediction
KW - Zoonoses
UR - http://www.scopus.com/inward/record.url?scp=85174190389&partnerID=8YFLogxK
U2 - 10.1017/S0950268823001553
DO - 10.1017/S0950268823001553
M3 - Article
SN - 1469-4409
VL - 151
SP - 1
EP - 10
JO - Epidemiology and Infection
JF - Epidemiology and Infection
M1 - e165
ER -