Mbuba Emmanuel, Mañas-Chavernas Natalia, Moore Sarah J, Ruzige Philipo David, Kobe Dickson, Moore Jason, Philipo Rose, Kisoka Noela, Pontiggia Gianpaolo, Chacky Frank, Mwalimu Charles Dismasi, Cattin Philippe Claude, Wolleb Julia, Sandkuehler Robin, Ross Amanda
Vector Control Product Testing Unit, Environmental Health and Ecological Science, Ifakara Health Institute, P.O. Box 74, Bagamoyo, United Republic of Tanzania.
Swiss Tropical and Public Health Institute, Kreuzstrasse 2, CH-4123, Allschwil, Switzerland.
Malar J. 2025 Mar 14;24(1):82. doi: 10.1186/s12936-025-05324-7.
The physical integrity of insecticidal-treated nets (ITNs) is important for creating a barrier against host-seeking mosquitoes and, therefore, influences people's perception of the net's effectiveness and their willingness to use it. Monitoring the physical integrity of ITNs over time provides information for replenishment schedules and purchasing decisions. Currently, the assessment of physical integrity of ITNs is conducted by manually counting holes and estimating their size to class the net as functional or not. This approach is laborious to routinely conduct during field surveys of ITNs. Automated image analysis may provide a rapid assessment of the physical integrity of ITNs but it is not known if the images can capture sufficient information. As a first step, this study aimed to assess the agreement between estimated hole surface areas derived from (1) manually segmented images, (2) manual hole counting compared to (3) ground truth obtained by calibrated close-up shots of individual holes.
The physical integrity of 75 ITNs purposely selected from an ongoing study was assessed by manual hole counting, image analysis and ground truth. For the image analysis, a graphical user interface was developed and used for the segmentation of holes visible in photographs taken from each side of the net. The hole surface area was then computed from this data. The agreement between the estimates from image analysis and manual hole counting was compared to the ground truth using the Bland-Altman method.
There was substantial agreement between the manually segmented image analysis estimates and the ground truth hole surface areas. The overall bias was small, with a mean ratio of the hole surface area from image analysis to the ground truth of 0.70, and the 95% limits of agreement ranging from 0.35 to 1.38. Manual hole counting underestimated the hole surface area compared to the ground truth, particularly among nets with holes above 10 cm in diameter.
Images coupled with manual segmentation contain sufficient information to calculate hole surface area. This lays the groundwork for incorporating automatic hole detection, and then assessing whether this method will offer a fast and objective method for routine assessment of physical integrity of ITNs. While the WHO method underestimated the hole surface area, it remains useful in classifying nets as either serviceable or too torn because the cut-off is specific to this method.
经杀虫剂处理的蚊帐(ITN)的物理完整性对于形成一道抵御寻找宿主蚊子的屏障至关重要,因此会影响人们对蚊帐有效性的认知及其使用意愿。长期监测ITN的物理完整性可为补充计划和采购决策提供信息。目前,对ITN物理完整性的评估是通过人工计数孔洞并估算其大小,以将蚊帐分类为是否可用。在对ITN进行实地调查时,这种方法按常规操作很费力。自动图像分析可能会提供对ITN物理完整性的快速评估,但尚不清楚图像能否捕捉到足够的信息。作为第一步,本研究旨在评估源自以下三种方法的估计孔洞表面积之间的一致性:(1)手动分割图像,(2)人工孔洞计数,以及(3)通过对单个孔洞的校准特写照片获得的真实情况。
从一项正在进行的研究中特意挑选了75顶ITN,通过人工孔洞计数、图像分析和真实情况评估其物理完整性。对于图像分析,开发了一个图形用户界面,并用于分割从蚊帐每一侧拍摄的照片中可见的孔洞。然后根据这些数据计算孔洞表面积。使用Bland-Altman方法将图像分析估计值与人工孔洞计数之间的一致性与真实情况进行比较。
手动分割图像分析估计值与真实孔洞表面积之间存在高度一致性。总体偏差较小,图像分析的孔洞表面积与真实情况的平均比值为0.70,一致性界限的95%范围为0.35至1.38。与真实情况相比,人工孔洞计数低估了孔洞表面积,尤其是在直径大于10厘米的孔洞的蚊帐中。
结合手动分割的图像包含计算孔洞表面积的足够信息。这为纳入自动孔洞检测奠定了基础,然后评估该方法是否会为ITN物理完整性的常规评估提供一种快速且客观的方法。虽然世卫组织的方法低估了孔洞表面积,但它在将蚊帐分类为可用或破损过度方面仍然有用,因为其截止值特定于此方法。