  The goal of threshold group testing is to identify up to $d$ defective items
among a population of $n$ items, where $d$ is usually much smaller than $n$. A
test is positive if it has at least $u$ defective items and negative otherwise.
Our objective is to identify defective items in sublinear time the number of
items, e.g., $\mathrm{poly}(d, \ln{n}),$ by using the number of tests as low as
possible. In this paper, we reduce the number of tests to $O \left( h \times
\frac{d^2 \ln^2{n}}{\mathsf{W}^2(d \ln{n})} \right)$ and the decoding time to
$O \left( \mathrm{dec}_0 \times h \right),$ where $\\mathrm{dec}_0 = O \left(
\frac{d^{3.57} \ln^{6.26}{n}}{\mathsf{W}^{6.26}(d \ln{n})} \right) + O \left(
\frac{d^6 \ln^4{n}}{\mathsf{W}^4(d \ln{n})} \right)$, $h = O\left( \frac{d_0^2
\ln{\frac{n}{d_0}}}{(1-p)^2} \right)$ , $d_0 = \max\{u, d - u \}$, $p \in [0,
1),$ and $\mathsf{W}(x) = \Theta \left( \ln{x} - \ln{\ln{x}} \right).$ If the
number of tests is increased to $O\left( h \times
\frac{d^2\ln^3{n}}{\mathsf{W}^2(d \ln{n})} \right),$ the decoding complexity is
reduced to $O \left(\mathrm{dec}_1 \times h \right),$ where $\mathrm{dec}_1 =
\max \left\{ \frac{d^2 \ln^3{n}}{\mathsf{W}^2(d \ln{n})}, \frac{ud
\ln^4{n}}{\mathsf{W}^3(d \ln{n})} \right\}.$ Moreover, our proposed scheme is
capable of handling errors in test outcomes.
