Lusiyana Novyan, Ahdika Atina
Department of Parasitology, Faculty of Medicine, Universitas Islam Indonesia, Jalan Kaliurang Km 14.5 Sleman, Yogyakarta, 55584, Indonesia.
Department of Statistics, Faculty of Mathematics and Natural Science, Universitas Islam Indonesia, Jalan Kaliurang Km 14.5 Sleman, Yogyakarta, 55584, Indonesia.
Infect Dis Model. 2022 Jun 6;7(3):261-276. doi: 10.1016/j.idm.2022.05.008. eCollection 2022 Sep.
The high prevalence of malaria in endemic areas generally stems from recurrence events, characterized by the appearance of malaria symptoms at the time of examination; nearly every resident is at risk of experiencing such a recurrence. The verified presence of sp is referred to as the Confirmed state, while the condition without confirmed is called the Undetected Parasitaemia state. After malaria treatment, a person can be in Aparasitaemic state or return to an Undetected Parasitaemia or Confirmed state due to non-adherence in complying with malaria therapy. In this study, we evaluate the characteristics of malaria recurrence in Timika, Indonesia, using the Markovian multiple-state model. In addition, we also simulate the probability of malaria recurrence after the implementation of several control strategies, including prevention strategies using insecticide-treated nets (ITNs) and indoor residual spraying (IRS).
This study aims to identify the transition probabilities of malaria recurrence with and without control strategies.
We use data from the medical records of malaria patients from the Naena Muktipura sub-health center in Timika, Papua, Indonesia, from March 2020 to March 2021. The data were grouped into two age categories: those under or over 24 years. The incidence of malaria in this area was modeled using a Markovian multiple-state model, dividing the incidence data based on the character of the patient's condition (Undetected Parasitaemia, Confirmed, or Aparasitaemic states) in order to obtain the patient's transition probabilities in each state. Furthermore, we simulate the recurrence probability given specific control strategies.
There were 964 visits to the sub-health center at Naena Muktipura in which symptoms of malaria were reported. Specifically, the number of the malaria incidences in the groups under and over age 24 were 456 and 508, respectively. The modeling results indicate that the probability of recurrence in the over-24 age group is generally higher than that in the under-24 age group. However, the probability of this recurrence decreases over time. Furthermore, providing a control strategy can reduce the probability of recurrence and increase the probability of recovery for these patients.
In endemic areas, adherence to treatment and preventive measures can accelerate the healing process and reduce the probability of malaria recurrence. With proper treatment management, the use of ITNs and the application of IRS, the incidence of malaria can be reduced and recovery can be accelerated.
疟疾流行地区的高发病率通常源于复发事件，其特征是在检查时出现疟疾症状；几乎每个居民都有经历这种复发的风险。疟原虫（sp）的确诊存在被称为确诊状态，而未确诊的情况则称为未检测到寄生虫血症状态。疟疾治疗后，由于不遵守疟疾治疗方案，一个人可能处于无寄生虫血症状态，或者回到未检测到寄生虫血症或确诊状态。在本研究中，我们使用马尔可夫多状态模型评估印度尼西亚蒂米卡疟疾复发的特征。此外，我们还模拟了实施几种控制策略（包括使用经杀虫剂处理的蚊帐（ITN）和室内滞留喷洒（IRS）的预防策略）后疟疾复发的概率。
本研究旨在确定有无控制策略时疟疾复发的转移概率。
我们使用了印度尼西亚巴布亚省蒂米卡纳纳穆克蒂普拉亚社区卫生中心2020年3月至2021年3月疟疾患者的医疗记录数据。数据分为两个年龄组：24岁以下和24岁以上。该地区的疟疾发病率使用马尔可夫多状态模型进行建模，根据患者病情特征（未检测到寄生虫血症、确诊或无寄生虫血症状态）对发病数据进行划分，以获得患者在每个状态下的转移概率。此外，我们模拟了给定特定控制策略时的复发概率。
纳纳穆克蒂普拉亚社区卫生中心有964次就诊报告了疟疾症状。具体而言，24岁以下和24岁以上组的疟疾发病率分别为456例和508例。建模结果表明，24岁以上年龄组的复发概率通常高于24岁以下年龄组。然而，这种复发的概率会随着时间降低。此外，提供控制策略可以降低复发概率，并提高这些患者的康复概率。
在疟疾流行地区，坚持治疗和预防措施可以加速康复过程并降低疟疾复发的概率。通过适当的治疗管理、使用经杀虫剂处理的蚊帐和实施室内滞留喷洒，可以降低疟疾发病率并加速康复。
