Pecharat Kitijarurat
Malaria is a highly infectious disease where parasites, such as p. falciparum, are transmitted by mosquitoes. The main cause for transmission of this disease is human transport through the high, and ever growing, connectivity between regions. This disease is currently prevalent in sub-Saharan Africa, where specific characteristics of Africa, such as ecological and environmental covariates, encourage the incubation of mosquitoes and parasites. Data science, such as the use of mobile phone data to map human movement, or satellite imaging to determine water sources, can help gather information needed to design and implement intervention methods for the elimination of this disease. However, resources and costs are often limited, thus the research question to be explored is: What is the most effective way of gathering, monitoring, and decision-making for decreasing malaria prevalence in sub-Saharan Africa?
“Mapping road network communities for guiding disease surveillance and control strategies” is a scientific article describing the relationship between road networks, communities, and connectivity, in the context of the spread of P. falciparum malaria and data science. The article highlights the significance of increasing human mobility in our modern age leading to increased movement of and introduction of pathogens through infected travelers. This is extremely dangerous, as this can lead to the start of epidemics infecting the many populations and communities. For example, there have been an increase in global transport networks, which in turn, increase pathogen movements by air, land, and sea; however, pathogens seem to move mainly by land. Overall, there is a rising global connectivity. Not only can high connectivity make epidemics more likely, but it can also lead to the spread of drug resistance.
Understanding how regions are connected through transport networks is extremely valuable for understanding how diseases spread. With this understanding, institutions can tailor disease prevention efforts to a specific target, making aid the most efficient it can be. A common problem, as a result of its complex nature, is encountered, which is that highly connected areas are consistently going past national borders. This calls into action that prevention efforts require multiple countries to cooperate with each other, as seen with P. falciparum malaria in Sub-Saharan Africa.
Analysing road networks to increase human development through health relates to Amartya Sen’s “Development as Freedom”. Amartya Sen views the healthcare aspect of human development as giving people the “basic freedom to survive.” In order to expand the real freedoms that people enjoy, there must be social and economic arrangements, such as facilities for health care, to provide people of basic freedoms first. With this article, the following sustainable development goals are considered: ensure health to promote well-being, and to strengthen the means of implementation and to revitalize global partnership.
In this particular case study, the African Road Network Data (ARN) was used to analyse communities and connectivity. This data is obtained by GPS navigation and cartography to map primary and secondary roads. For data on malaria prevalence and population maps, the data was obtained from the Malaria Atlas Project. This data was created by using 5x5 km grid cells for prevalence of P. falciparum across Africa multiplied by aggregated 1x1 km population data (from WorldPop) to obtain an estimated number of infections per 5x5 km grid cell. With these methods, the authors are investigating how communities, populations, and roads can affect the spread of infectious diseases that can disturb the overall well-being of a region. Overall, the authors are trying to reach the full understanding between connectivity, transport, with the spread of infectious diseases.
“Malaria prevalence metrics in low- and middle-income countries: an assessent of precision in nationally-representative surveys” is a scientific article examining the factors which go into the precision of national-level surveys such as the census. Examining the effectiveness and precision of such surveys is very important because the data from these surveys often serve as the basis for data science analysis, and furthermore, healthcare interventions. Surveys are typically time-consuming, use a lot of resources and cost a lot of money, so examining them can lead to a survey-design which maximizes effectiveness. The potential harm outlined in this study is the errors that could be made by having incorrect sample sizes in the process of estimation of disease prevalence, specifically with examples of malaria in sub-Saharan Africa. This topic is significant because there is an increasing demand for reliable, high quality data to support decision-making and progress towards sustainable development goals, especially in low-middle income countries. Surveys are a good source of this data because they provide timely information with high resource availability. Nationally-representative surveys are the main source of data for establishing a scientific evidence base, monitoring disease, and evalutation of overall healthcare, but sometimes the surveys do not focus enough on the importance of defining indicator-relevant sample sizes to have high precision.
This relates to Amartya Sen’s idea that adequate investment and economic support is crucial for human development. In the context of this study, the authors emphasize that current surveys need additional investment to become more successful and efficient. For example, in 2015, in the analysis of the Kenya MIS (malaria indicator surveys), and the intra-class correlation (ICC) suggested that large sample sizes are required for high precision. Thus, authorities need to design a more cost-effective way to implementing cross-sectional surveys to reach a level of precision that is accurate for analysis. The dimension of human development being addressed by the authors’ research is infectious disease epidemiology and health advocacy for health interventions. The two main sustainable goals focused here is to ensure healthy lives and well-being for all ages, and also to streghthen cooperation between countries. In this scientific article, these people are generating data sets; sampling was performed with ArcGIS 10 using a spatial random sampling design tool based on a sampling seed. Geographical coordinates are also logged with most of the data they receive from sampling in the field. The authors are investigating the process of nationally-representative surveys in the progression of human health development. Overall, the question that this source is trying to address is, how can data scientists reach the highest precision of disease prevalence from nationally-representative surveys? The authors go on to explain that it has to deal with variability at the cluster level, and how it has an impact on how large a sample size should be for indicators of malaria.
This research paper has the purpose of trying to understand how and when to use interventions, and combine them, in the context of malaria vectors in sub-Saharan Africa. Malaria is a deadly infectious disease, responsible for killing several populations in sub-Saharan Africa; however, with an increase in effective malaria control since 2000, there has been a decline in malaria morbidity and mortality. This study aims to understand how interventions can be designed to maximize its impact of malaria vectors by specifically assessing the effect of indoor residual spraying on malaria vector densities in area where the use of long-lasting insecticidal nets (LLINs) were high. This paper is of significance because understanding how to maximize the impact of interventions will save resources, time, and money. Interventions, such as the government-mass campaigns and government-initiated indoor residual spraying (IRS) campaigns, require a reliable scientific evidence basis, usually gathered by surveys and data-science methodological analyses. For example, in the study, they were able to establish seasonal peaks in malaria venctor densities, and these pieces of data provide guidance for targeting IRS before peak transmission.
In this particular case study, all households who were enrolled in the malaria study in 2011 were provided with LLINs; and in neighboring communities, the proportion of those households with at least one LLINs increased in the next few years. Unfortunately, this one act did not significantly decrease mosquito density (only did it have an effect when combined with IRS), but it does support Amartya Sen’s idea that government and the authoritative institutions of regions should provide aid to those who need it. In other words, intervention and aid need to be provided so populations in those communities can have access to freedom, and that is the basic freedom to survive. Moreover, the dimension of human development being addressed here is cross-national healthcare, specifically with malaria vector species. The sustainable development goals focused in this article are to ensure healthy lives and promote well-being for all ages, and to strengthen the means of implementation and revitalize global partnership for sustainable development.
In this study, vector control is the main focus, and is central to the Global Technical Strategy (GTS) by the Global Malaria Programme. The methods include gathering data from multi-country analysis based on nationally-representative households surveys from DHS and MIS in sub-Saharan Africa. The heterogenious distribution of mosquitoes was studied through a longitudinal study in Nagongera, Uganda. Linear regression and the Bayesian information criterion (BIC) checked correlations between covariates which affects mosquito counts. These calculations were then mixed with spatial-temporal effected used to predict continuous maps of vector densities. Thus, the human development process that the authors are investigating is spatial epidemiology with the scientific question: which combinations of malaria interventions produce the maximal impact on malaria vector densities, and when should they be implemented? This study concluded that IRS using bendiocarb spray proved to have complemented high LLIN coverage, but it has to be associated with continuous monitoring of insecticide resistance.
“Quantifying the Impact of Human Mobility on Malaria” is a scientific report exploring the significance of human movements as the main cause of transmission of malaria parasites on large spatial scales. Furthermore, this report outlines the use of mobile phones in sub-Saharan African regions, specifically Kenya, to identify “hot spots” of the malaria epidemic. Instead of surveying people for their travel patterns, data scientists can use individual-level longitudinal data collected by mobile phones to determine human movements on a much larger scale in a timely, cheap manner. The report dives into the different variables and outcomes using mobile phone data to specifically identify dynamics of human carriers that allow for parasite importation and transmission between regions in Kenya. The related harm associated with this report is the high likelihood of infection by plasmodium falciparum in areas near Lake Victoria, Kenya. The significance of this issue is that transmission and importation of the malaria parasite vector by human movement increase drastically beyond what would be possible for mosquitoes alone. The transmission and importation of malaria occurs by which the authors categorize as returning residents, passive acquirers and active transmitters. In essence, these are individuals who visit endemic areas and carry parasites back to their primary settlements, or those individuals who carry parasites when they visit other settlements. The report stresses that intervention strategies should ideally focus on the importation of the parasite versus focusing on malaria prevalence itself.
Understanding the impact of human mobility helps design intervention methods to prevent malaria and this leads to the expansion of freedoms for the relevant populations. This relates to Amartya Sen’s definition of human development as freedom. The freedoms include the basic freedom to survive, and the freedom to travel to areas where they wish. One method to initiate this is by using mobile phone data to map human transport networks. However, there are limitations to using mobile phone data. For example, mobile phone data can only measure mobility of individuals where there are cell towers, so it would not be able to map cross-border migration, or it would underrepresent individuals in poorer regions who are not located near cell towers. Although mobile phone data has its limitations, it has been used to analyze nearly 15 million individuals in Kenya to map human movement. Every phone call and text made to the cell towers located within the boundaries of the study was mapped and defined by satellite images. This was done by assigning each individual to a primary settlement, and calculations were made based on destination and duration in and out of their primary settlement. The sustainable development goals considered are health related. The human development pattern that the authors are investigating is epidemiology based on human movement. Overall, the scientific question the authors are seeking to answer is: which regions are sources for malaria transmission and importation, and in what instances does this occur?
This scientific article explored the most efficient way of identifying key sources of malaria for the elimination of malaria. The authors call for a new, more accurate method to measuring progress, and practical information that can be used to direct and optimize scare resources due to heterogeneity of malaria in the sub-Saharan African country of Swaziland. The big idea in this report is that in order to design effective, targeted intervention strategies, assessments must be made both of receptivity and vulnerability so that actual, actionable information/data can be used to support these programs. The harm explored in this article is of malaria as the leading cause of childhood morbidity and mortality. Malaria also has the impact to complicate diagnosis and treatments of other existing diseases for individuals. There has been significant success in Swaziland; according to the Swaziland National Malaria Control Program (NMCP), malaria has declined from 2.9 to 0.07 malaria cases per 1000 people since 1999. Malaria is a complex situation in sub-Saharan Africa due to high spatial heterogeneity caused by a variety of factors that are environmental and ecological.
One of the ideas the authors stated is that Swaziland should be responsible of identifying regions that are missed during surveys for case detection. This relates to Amartya Sen’s idea that governments and institutions should provide aid, such as vaccine coverage and outbreak resources, and interventions to help ensure that people get help, giving them the freedom to live, which in turn, can lead to a progression in human development in these areas. The sustainable development goal focused here is health care. One dataset used by authors is obtained by surveillance data. The Lubombo Spatial Development Initiative (LSDI) works in Swaziland to identify household loactions confirmed with malaria through case detection, and this is georeferenced by the (NMCP). Spatio-temporal associations are also developed using algorithms to reconstruct transmission chains, using data from the NMCP to identify potential causal links. In addition to this method, they aggregate movements of mosquitoes and individuals. Another aspect of their methodology is modelling malaria receptivity. Malaria receptivity is the potential for ongoing local transmission, defined quantitatively by the effective reproduction number, Rc. The number of parasite offspring at each case location is defined by spatial covariates such as weatherm geography, population densitym and urbanicity. They produce the topographic wetness index (TWI) to help support findings in numbers because of the direct relationship between water and number of offspring. The normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) is calculated from the Landsat Enhanced Thematic Mapper (ETM). Overall, the question they are trying to address is: how to stratify Swaziland to allocate resources in the most efficient manner within a country. The authors propose that the NMCP needs to manage transmission between endemic neighboring countries by directing and optimizing the limited resources they have. To do so, they suggest that combining assessments of receptivity with vulnerability will provide use information, such as spatiotemporally relevant metrics of transmission, to support malaria targeted programs.
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