## 4 Discussion  
### Fish Diseases Correlation with Climate Change  
Global climate change can affect the ecological settings for pathogens and hosts, involving aspects such as immunity and transmission pathways. Artificial intelligence systems have yet to be used for diagnosis in aquatic animal veterinary clinics around the world. To date, only a few groups have developed useful software programs, e.g., Fish-Vet [21] and Fish-Expert [22]. Studies show that the field of aquatic animal disease is constantly changing and developing [23]. Due to growing environmentally harmful human activities, the concentration of greenhouse gases such as carbon dioxide (CO\({}_{2}\)) and methane (CH\({}_{4}\)) in the atmosphere has increased, leading to an increase in the greenhouse effect, global  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Rainfall**} & \multirow{2}{*}{**B**} & \multirow{2}{*}{**S.E.**} & \multirow{2}{*}{**df**} & \multirow{2}{*}{**Sig.**} & \multirow{2}{*}{**Exp (B)**} & \multicolumn{2}{c}{**95.5\% C.I. EXP(B)**} \\ \cline{5-8}  & & & & & & **Lower** & **Upper** \\ \hline
0 day \({}^{*}\) & 0.488 & 0.203 & 1 & 0.016 & 1.630 & 1.095 & 2.426 \\
3 day \({}^{*}\) & 0.406 & 0.201 & 1 & 0.043 & 1.501 & 1.012 & 2.227 \\
5 day & 0.256 & 0.197 & 1 & 0.195 & 1.291 & 0.877 & 1.901 \\
10 day & \(-\)0.052 & 0.212 & 1 & 0.806 & 0.949 & 0.626 & 1.439 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Univariate logistic regression analysis of the rainfall in different days before the occurrence of tilapia streptococcosis.  
Figure 5: The relations between the percentage of cumulated positive farms from all submitted tilapia cases and climate factors: (**A**) average atmospheric pressure; (**B**) average temperature; (**C**) UV index. When the average temperature is 27.0 \({}^{\circ}\)C, the average atmospheric pressure is 1005.1 hPa, or the UV index is 7.2, the percentage of cumulated positive farms from all submitted tilapia cases reached 50%.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Climate Factor**} & \multirow{2}{*}{**B**} & \multirow{2}{*}{**S.E.**} & \multirow{2}{*}{**df**} & \multirow{2}{*}{**Sig.**} & \multirow{2}{*}{**Exp (B)**} & \multicolumn{2}{c}{**95.5\% C.I. EXP(B)**} \\ \cline{5-8}  & & & & & & **Lower** & **Upper** \\ \hline Average atmospheric & \(-\)0.043 & 0.026 & 1 & 0.090 & 0.958 & 0.911 & 1.007 \\ pressure (hPa) & \(-\)0.014 & 0.039 & 1 & 0.727 & 1.014 & 0.939 & 1.095 \\ Average temperature (\({}^{\circ}\)C) & 0.069 & 0.047 & 1 & 0.145 & 1.071 & 0.977 & 1.175 \\ Wallinall & 0.325 & 0.216 & 1 & 0.133 & 1.384 & 0.906 & 2.114 \\ constant & 41.653 & 26.315 & 1 & 0.113 & \(1.229\times 10^{18}\) & & \\ \hline \hline \end{tabular}
\end{table}
Table 3: Multivariate logistic regression analysis on tilapia streptococcosis and climatic factors.  
warming, and sea levels, resulting in an imbalance in the ecosystem. Among the climatic factors, correlation between increasing water temperature and risk of fish disease was a diagnostic factor for parasitic infections but not for bacterial or viral infections [11]. A 23-year-long study on the assessment of disease dynamics at a salmon farm in Finland showed that ecological changes, especially changes in temperature, increased the prevalence of the disease caused by _Flavobacterium columnar_ during the high temperature season [24]. Additional research has reported streptococcus outbreaks to be more closely related to intensive farming, high water temperature (especially summer time), and water quality than the incidence of the pathogen itself [19; 25; 26].