Understanding reproductive health challenges during a flood: insights from Belkuchi Upazila, Bangladesh [version 1; peer review: 2 approved]

Background: Bangladesh is exposed to natural hazards such as floods, cyclones and droughts. As such, its health systems and health infrastructure are exposed to recurrent disasters. Research studying the impacts of natural disasters on reproductive health in particular is lacking. This research contributes to this knowledge gap by studying the challenges related to menstrual regulation and post-abortion care at both the facility and community levels, and the care-seeking patterns of pregnant women during the 2016 flood in Belkuchi, Bangladesh. Methods: Six government-run primary health care facilities were assessed using a structured assessment tool prior to the flood of 2016. In total, 370 structured interviews were conducted with women in three unions of Belkuchi (Belkuchi Sadar, Daulatpur and Bhangabari) 4 months after the 2016 flood. Results: The main challenges at the facility level are a lack of services and a shortage of medicines, equipment and trained health workers. The main challenges at the community level are displacement, high rates of self-diagnosed spontaneous abortion and a lack of treatment for post-abortion complications. A majority of the interviewed women (48%) sought menstrual regulation from the residence of a nurse or family welfare visitor. In total, 73.2% of the women who experienced post-abortion complications sought medical care. Conclusion: To overcome the challenges at the facility level, it is important to construct flood-resistant health infrastructure and train health workers in menstrual regulation and post-abortion care, so that these services can be made available during a flood. At the community level, more research is required to understand the reasons for spontaneous abortions so that these, and the subsequent chronic conditions/complications women experience, may be avoided. Context specific interventions that can overcome local challenges (both at the community and facility levels) are required to promote disaster resilience at primary health care facilities

On-demand fuzzy clustering and ant-colony optimisation based mobile data collection in wireless sensor network

In a wireless sensor network (WSN), sensor nodes collect data from the environment and transfer this data to an end user through multi-hop communication. This results in high energy dissipation of the devices. Thus, balancing of energy consumption is a major concern in such kind of network. Appropriate cluster head (CH) selection may provide to be an efficient way to reduce the energy dissipation and prolonging the network lifetime in WSN. This paper has adopted the concept of fuzzy if-then rules to choose the cluster head based on certain fuzzy descriptors. To optimise the fuzzy membership functions, Particle Swarm Optimisation (PSO) has been used to improve their ranges. Moreover, recent study has confirmed that the introduction of a mobile collector in a network which collects data through short-range communications also aids in high energy conservation. In this work, the network is divided into clusters and a mobile collector starts from the static sink or base station and moves through each of these clusters and collect data from the chosen cluster heads in a single-hop fashion. Mobility based on Ant-Colony Optimisation (ACO) has already proven to be an efficient method which is utilised in this work. Additionally, instead of performing clustering in every round, CH is selected on demand. The performance of the proposed algorithm has been compared with some existing clustering algorithms. Simulation results show that the proposed protocol is more energy-efficient and provides better packet delivery ratio as compared to the existing protocols for data collection obtained through Matlab Simulations