Modeling the relationship between malaria prevalence and insecticide-treated bed net coverage in Nigeria using a Bayesian spatial generalized linear mixed model with a Leroux prior

Okunlola, Oluyemi A.; Oyeyemi, Oyetunde T.; Lukman, Adewale F.

doi:10.4178/epih.e2021041

Cited by 7 publications

(10 citation statements)

References 26 publications

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“…The spread of malaria and anaemia in Nigeria has been a concern to researchers which has led to several studies such as [12,[16][17][18][19][20]. In [21], a quasi-experimental fixedeffect model was used to investigate the effect of malaria on haemoglobin concentration in children under 5 years old.…”

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confidence: 99%

Bayesian spatio-temporal modelling and mapping of malaria and anaemia among children between 0 and 59 months in Nigeria

Ibeji

Mwambi

Iddrisu

2022

Malar J

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Background/M&M A vital aspect of disease management and policy making lies in the understanding of the universal distribution of diseases. Nevertheless, due to differences all-over host groups and space–time outbreak activities, data are subject to intricacies. Herein, Bayesian spatio-temporal models were proposed to model and map malaria and anaemia risk ratio in space and time as well as to ascertain risk factors related to these diseases and the most endemic states in Nigeria. Parameter estimation was performed by employing the R-integrated nested Laplace approximation (INLA) package and Deviance Information Criteria were applied to select the best model. Results In malaria, model 7 which basically suggests that previous trend of an event cannot account for future trend i.e., Interaction with one random time effect (random walk) has the least deviance. On the other hand, model 6 assumes that previous event can be used to predict future event i.e., (Interaction with one random time effect (ar1)) gave the least deviance in anaemia. Discussion For malaria and anaemia, models 7 and 6 were selected to model and map these diseases in Nigeria, because these models have the capacity to receive strength from adjacent states, in a manner that neighbouring states have the same risk. Changes in risk and clustering with a high record of these diseases among states in Nigeria was observed. However, despite these changes, the total risk of malaria and anaemia for 2010 and 2015 was unaffected. Conclusion Notwithstanding the methods applied, this study will be valuable to the advancement of a spatio-temporal approach for analyzing malaria and anaemia risk in Nigeria.

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confidence: 99%

Bayesian spatio-temporal modelling and mapping of malaria and anaemia among children between 0 and 59 months in Nigeria

Ibeji

Mwambi

Iddrisu

2022

Malar J

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“…Of the total of 52 studies, 26 (50.0%) were on infectious diseases, 11 (21.1%) on malaria [ 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 ], 8 (15.3%) on Dengue fever [ 40 , 41 , 42 , 43 , 44 , 45 ], 4 (7.6%) on HIV [ 46 , 47 , 48 , 49 ], and 3 (5.7%) on TB [ 50 , 51 , 52 ]. Overall, 10 (19.2%) studies were on chronic diseases [ 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 ], 8 (15.5%) on maternal and child health [ 63 , 64 , 65 , 66 ], 3 (5.7%) on nutrition [ 67 , 68 , 69 ] and 5 (9.6%) were applied to other health-related outcomes [ 58 , 70 , 71 , 72 , 73 ].…”

Section: Resultsmentioning

confidence: 99%

“…The number of spatial units in the reviewed studies ranged from a minimum of 10 to a maximum of 1325. About 9 (17.3%), 7 (13.1%), 6 (11.5%), and 6 (11.5%) studies’ spatial unit of analysis were districts [ 37 , 44 , 46 , 56 , 62 , 68 , 74 , 81 ], counties [ 32 , 34 , 48 , 49 , 52 , 75 , 77 , 78 ], regions [ 30 , 31 , 38 , 59 , 72 , 80 ], and provinces [ 35 , 41 , 45 , 50 , 51 , 53 ], respectively. The majority of the studies (80.7%) used years as a temporal unit measure and 9 (17.3%) studies used months as a temporal unit measure.…”

Section: Resultsmentioning

confidence: 99%

“…The majority of the studies (80.7%) used years as a temporal unit measure and 9 (17.3%) studies used months as a temporal unit measure. A total of 46 (88.5%) studies used the MCMC estimation technique for their Bayesian modelling [ 31 , 32 , 33 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 54 , 55 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 ] and 6 (11.5%) studies used INLA as their estimation technique [ 30 , 34 , 53 , 56 , 66 , 67 ].…”

Section: Resultsmentioning

confidence: 99%

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A Systematic Review of Areal Units and Adjacency Used in Bayesian Spatial and Spatio-Temporal Conditional Autoregressive Models in Health Research

Tessema

Tesema

Ahern

et al. 2023

IJERPH

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Advancements in Bayesian spatial and spatio-temporal modelling have been observed in recent years. Despite this, there are unresolved issues about the choice of appropriate spatial unit and adjacency matrix in disease mapping. There is limited systematic review evidence on this topic. This review aimed to address these problems. We searched seven databases to find published articles on this topic. A modified quality assessment tool was used to assess the quality of studies. A total of 52 studies were included, of which 26 (50.0%) were on infectious diseases, 10 (19.2%) on chronic diseases, 8 (15.5%) on maternal and child health, and 8 (15.5%) on other health-related outcomes. Only 6 studies reported the reasons for using the specified spatial unit, 8 (15.3%) studies conducted sensitivity analysis for prior selection, and 39 (75%) of the studies used Queen contiguity adjacency. This review highlights existing variation and limitations in the specification of Bayesian spatial and spatio-temporal models used in health research. We found that majority of the studies failed to report the rationale for the choice of spatial units, perform sensitivity analyses on the priors, or evaluate the choice of neighbourhood adjacency, all of which can potentially affect findings in their studies.

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“…Malaria is still being actively transmitted across African countries, however, observations from our study showed that the various interventional programmes could be yielding expected results as there was a significant decrease in malaria incidence in about 81% of the observed African countries. Increase insecticide-treated nets (ITNs) coverage across African countries over the years may be responsible for this malaria decline [ 21 , 22 ]. The use of ITNs may result in a decline in the population of indoor Anopheles mosquitoes by triggering behavioural changes in biting and resting of mosquitoes including a shift from an indoor to an outdoor environment [ 23 ].…”

Section: Discussionmentioning

confidence: 99%

Malaria transmission in Africa: Its relationship with yellow fever and measles

Okunlola

Oyeyemi

2022

PLoS ONE

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Background Malaria has been strongly linked to the transmission and pathophysiology of some viral diseases. Malaria and vaccine-preventable diseases often co-exist in endemic countries but the implication of their co-existence on their transmission dynamics and control is poorly understood. The study aims to evaluate the relationships between the incidence of malaria and cases of measles and yellow fever in Africa. Methods The malaria incidence, death due to malaria, measles and yellow fever data were sourced from the WHO database. Poisson and zero-inflated time-trend regression were used to model the relationships between malaria and the two vaccine-preventable diseases. P-values <0.05 were considered statistically significant. Results A significant negative relationship existed between malaria incidence and measles cases (P<0.05), however, malaria showed a positive relationship with yellow fever (P<0.05). The relationships between death due to malaria and measles/yellow fever cases followed similar trends but with a higher level of statistical significance (P<0.001). Conclusions Malaria varied negatively with measles cases but positively with yellow fever. The relationships observed in this study could be important for the management of malaria and the studied vaccine-preventable diseases. Increase vaccination coverage and/or malaria treatment could modulate the direction of these relationships.

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Modeling the relationship between malaria prevalence and insecticide-treated bed net coverage in Nigeria using a Bayesian spatial generalized linear mixed model with a Leroux prior

Cited by 7 publications

References 26 publications

Bayesian spatio-temporal modelling and mapping of malaria and anaemia among children between 0 and 59 months in Nigeria

Bayesian spatio-temporal modelling and mapping of malaria and anaemia among children between 0 and 59 months in Nigeria

A Systematic Review of Areal Units and Adjacency Used in Bayesian Spatial and Spatio-Temporal Conditional Autoregressive Models in Health Research

Malaria transmission in Africa: Its relationship with yellow fever and measles

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