Dengue fever, a vector-borne disease spread by bites of infected female Aedes mosquitoes, has spread globally with several outbreaks. Thus, understanding the life cycle of Aedes mosquitoes, reproduction, transmission mechanisms, and weather variables is crucial for effective control of mosquitoes and surveillance of dengue fever. This paper systematically presents a novel stochastic agent-agent-based model implemented using GAMA 1.9.2 that simulates the transmission dynamics of dengue virus and the life cycle of Aedes Aegypti mosquito in low-resource environments in Dar es Salaam-Tanzania. The simulation results indicated that changing weather parameters influenced the vector population dynamics. The vector population increased gradually when weather conditions were favourable and vice versa. The simulation results revealed a continuous dengue prevalence throughout the year, indicating a silent spread of dengue. During the silent spread of dengue, it may be optimal to intervene in mosquito production at the egg and larva stages and eradicate adult mosquitoes.

African countries need to strengthen surveillance and control of arboviral diseases such as dengue due to increased outbreaks and spread of arboviruses. Climatic, socio-environment, and ecological variables influence the spread of dengue fever in Sub-Saharan Africa. This paper presents an Agent-Based conceptual and design model for dengue fever developed using the Multi-Agent Research and Simulation (MARS) framework. The study analyzes dengue fever's spatial distribution and identifies the causal relationship between the disease and its climatic and environmental variables. Agent-based modeling (ABM) was used to comprehend the spatial patterns of variation to determine the ecological association between the observed spatio-temporal variations in dengue fever. The domain and design model of an ABM for the surveillance of dengue fever is presented based on the Overview, Design Concepts, and Details (ODD) protocol. Model input parameters and input data for the study area are also presented. The dengue ABM can be adopted and reused for modeling other diseases and other complex problems from different domains while ensuring that their unique characteristics and appropriate modifications are considered to ensure the model's validity and relevance to the new context.

The study sought to review the works of literature on agent-based modeling and the influence of climatic and environmental factors on disease outbreak, transmission, and surveillance. Thus, drawing the influence of environmental variables such as vegetation index, households, mosquito habitats, breeding sites, and climatic variables including precipitation or rainfall, temperature, wind speed, and relative humidity on dengue disease modeling using the agent-based model in an African context and globally was the aim of the study. A search strategy was developed and used to search for relevant articles from four databases, namely, PubMed, Scopus, Research4Life, and Google Scholar. Inclusion criteria were developed, and 20 articles met the criteria and have been included in the review. From the reviewed works of literature, the study observed that climatic and environmental factors may influence the arbovirus disease outbreak, transmission, and surveillance. Thus, there is a call for further research on the area. To benefit from arbovirus modeling, it is crucial to consider the influence of climatic and environmental factors, especially in Africa, where there are limited studies exploring this phenomenon.

Mobile phone technology has invaded people's daily routine. The improvements in this technology have facilitated its use in different areas including the health sector. As a result, mobile phones are found to be more useful in areas where the use of road or postal systems often delay or are unsuitable for data communication. This study analysed and documented the requirements needed for the design and development of a smartphone-based application that is used for reporting of routine health data from the primary health facilities to district level in a Sub-Saharan country. Qualitative data collection methods have been used to gather correct, consistent, unambiguous, complete, relevant and testable system requirements. In the conceptual modelling entity relationship diagram, class diagram, use cases, sequence diagram and cross-functional flow chart diagram have facilitated the designing and development of the user interfaces of the smartphone-based reporting application.

This study focuses on improving the routine reporting of health data by identifying the challenges associated with timely reporting of routine data from the primary health facilities to the district and determines how mobile phones can be used to overcome the problem and thus enhance information use for action at all levels of the health system. Findings have indicated that, timely reporting of routine health data face challenges such as poor infrastructure, remoteness of the health facilities from the district where they have to submit their reports as well as transport costs that health workers have to incur in order to submit their report. Facing these challenges, this research revealed that the use of mobile phone application built in the District Health Information System database can provide an easy, cost effective and reliable means for reporting of health data. Over a period of 5 months, the data completeness and timeliness improved from 50% to 89%. This implies that the routine reporting of around ten data elements through mobile phones is feasible. The study recommends rigorous supervision, which among other things checks for data quality and correctness.