Using Weather Forecasts to Help Manage Meningitis in the West African Sahel

Pandya, Rajul; Hodgson, Abraham; Hayden, Mary H.; Akweongo, Patricia; Hopson, T. M.; Forgor, Abudulai Adams; Yoksas, T.; Dalaba, Maxwell Ayindenaba; Dukić, Vanja; Mera, Roberto; Dumont, Arnaud; McCormack, Kristen; Anaseba, Dominic; Awine, Timothy; Boehnert, Jennifer; Nyaaba, Gertrude Nsorma; Laing, Arlene; Semazzi, Fredrick H. M.

doi:10.1175/bams-d-13-00121.1

Cited by 14 publications

(17 citation statements)

References 38 publications

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“…Mean monthly absolute humidity shows a less pronounced seasonal trend (Figure , Table ), with Mwanza displaying a slightly different regime. As with temperature a clear altitudinal relationship can be seen for mean monthly absolute humidity, with Mbeya (1704m amsl) experiencing the overall lowest values, which, from June to September, drop below 10gm −3 – a key value associated with the onset of bacterial meningitis (Cheesbrough et al ., ; Pandya et al ., ). Dar es Salaam (55m amsl) experiences the highest absolute humidity.…”

Section: Resultsmentioning

confidence: 99%

“…Mbeya’s baseline absolute humidity demonstrates suitable conditions for meningococcal meningitis of 10gm −3 for 4 months per year, with the lowest observed values consistently being recorded below 10gm −3 (Figures (d)). Whilst conditions seem appropriate for what is considered to be the most influential factor with regards to meningococcal meningitis distribution, no records for the disease have currently been observed in this location, suggesting that other relevant climatic factors may not currently be suitable; however, further analysis should be conducted (Pandya et al ., ). Furthermore, reductions in maximum absolute humidity and increased exacerbation in humidity trends from June to September further increase the suitability for meningococcal meningitis transmission within these months.…”

Section: Resultsmentioning

confidence: 99%

“…Climatic conditions play a key role in the formation of suitable habitats and conditions for disease transmission and epidemic outbreaks to occur (Pandya et al ., ). vector‐borne diseases such as malaria are particularly influenced by climatic conditions due to the temperature‐dependent nature of the mosquito lifecycle (the mosquito being the dominant transmitter of malaria), as well as the vectors’ habitat suitability (Killeen and Chitnis, ).…”

Section: Introductionmentioning

confidence: 99%

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The local response of El Niño events and changing disease distribution in Tanzania

Reynolds

Cavan

Cresswell

2017

Weather

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Climate is a key determinant of a number of disease pathogen lifecycles and disease transmission processes, particularly within tropical climates such as that experienced in Tanzania. Over recent decades, climate‐related diseases such as malaria, chikungunya and bacterial meningitis have shown notable changes in their spatial distribution, with instances of both re‐emergence and expansion beyond previously known boundaries being recorded. The unpredicted change in disease distribution already experienced in Tanzania has placed a significant burden on health systems and available resources, and whilst a number of factors are involved, climate remains the least understood aspect within epidemiological changes. Here we examine how climate extremes – particularly El Niño events – influence key environmental and climatic elements which promote epidemiological expansion. This study investigates the baseline climatology in five of Tanzania’s varying climatological regions using the Met Office MIDAS dataset for the period 1985–1995. Its aim is to characterise the average climate and investigate the impacts of El Niño on the climatology of these regions, and to explore associated changes in disease distribution to allow identification, in the present, of changes which are anticipated to occur in the future to be put into context. The years 1997 and 2015 are used to examine the climate extremes imposed by El Niño events through statistical comparison methods. The results demonstrate that average climate conditions vary beyond previously documented observations, with each region of Tanzania responding differently to the onset of El Niño, thus potentially promoting a spatially variable disease response. These results are particularly marked for areas of greater climatic and environmental sensitivity within Tanzania. Once further understood, knowledge of this relationship could be applied to more local analysis and aid in predicting future outbreaks within Tanzania.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The local response of El Niño events and changing disease distribution in Tanzania

Reynolds

Cavan

Cresswell

2017

Weather

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“…Pandya et al . () modelled the transmission of meningitis using a differential‐equation‐based epidemiological model with epidemiological data and meteorological variables from 2007 to 2009, and determined the co‐efficients. The resulting linear finite difference equation relates the change in the number of new cases of meningitis to the number of cases in previous weeks.…”

Section: Introductionmentioning

confidence: 99%

Relationship between meteorological variables/dust and the number of meningitis cases in Burkina Faso

Nakazawa

Matsueda

2017

Meteorological Applications

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Using four meteorological variables (northeasterly surface wind (WS), relative humidity (RH), rainfall (Rain) and temperature (T2m)) and one of four dust products (dust surface mass concentration or aerosol optical depth, D1–D4) over Burkina Faso, a differential equation for meningitis incidence (N) was applied to the multivariate log‐linear regression analysis to get each contribution from the variables (WS, RH, Rain, T2m and one of four dust products) to N. The climatological data show that dust and temperature are synchronized with meningitis incidence, but the meningitis incidence reaches a peak several months after the northeasterly wind becomes maximum and the relative humidity becomes minimum during the no‐rain period. That is, meningitis incidence increases when the northeasterly wind prevails under dry and no‐rain conditions and decreases when the southwesterly wind prevails under wet and rain conditions, and it has a peak under dusty and hot conditions. After performing all possible combinations of the regression analysis (but choosing only one dust dataset for each combination) using models with one to five parameters, the time derivative of the weekly meningitis incidence from 2006 to 2014 was estimated and compared with that observed. The more parameters that are included, the higher the correlation co‐efficients between the estimated and observed tendency. However, the northeasterly wind has a major contribution to the rate of change of the number of cases. The highest correlation co‐efficient was for the models with all four meteorological variables plus the dust surface mass concentration data. Even in one‐ or two‐parameter models, a maximum correlation co‐efficient of 0.666 is obtained for the WS model, and the WS + RH model gives a maximum of 0.754, which indicates some forecast skill using surface wind and relative humidity data. Although the modelled derivative underestimated the outbreaks in 2006 and 2007, it correctly simulated the timing of the zero crossing of the weekly rate of change of N. Thus, this approach may be useful to identify the timing of the peak season of meningitis in Burkina Faso.

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“…This makes the ITD especially important in the Sahel, whose inhabitants are heavily dependent on rain-fed agriculture. Additionally, the collapse of seasonal outbreaks of meningitis that affect the Sahel have been shown to be strongly linked to increases in humidity associated with northward surges of the monsoon flow (Mera et al 2014;Pandya et al 2015). These impacts on West African meteorology mean that there is great value in understanding the behavior of the ITD in models, observations, and such widely used products as operational analysis and reanalysis datasets.…”

Section: Introductionmentioning

confidence: 99%

Disagreements in Low-Level Moisture between (Re)Analyses over Summertime West Africa

Roberts

Marsham

Knippertz

2015

Monthly Weather Review

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Reanalysis and operational analysis products are routinely used as the best estimates of the atmospheric state for operational and research purposes. However, different models, assimilation techniques, and assimilated datasets lead to differences between products. Here, such differences in the distribution of low-level water vapor over summertime West Africa are analyzed, as reflected in the zonal mean position of the leading edge of the West African monsoon [the intertropical discontinuity (ITD)] using five reanalyses [NCEP-NCAR, NCEP-Department of Energy (DOE), the Modern-Era Retrospective Analysis for Research and Applications (MERRA), the Climate Forecast System Reanalysis (CFSR), and the Interim ECMWF ReAnalysis (ERA-Interim)] and two operational analyses [Global Forecast System (GFS) and ECMWF] during the 11 monsoon seasons (April-September) from 2000 to 2010. Specific humidity differences regularly reach 50% of the mean value over areas spanning hundreds of kilometers and often coincide with northward excursions of the ITD that last several days and bring unusual rainfall to the Sahel and Sahara. The largest disagreements occur during the southward retreat of the ITD and are connected with anomalously high values of aerosol optical depth, consistent with the production of haboob dust storms. The results suggest that known errors in the representation of moist convection and cold pools may contribute to the identified disagreements. A large reduction in disagreement occurs in 2006, when upper-air observations were enhanced during the African Monsoon Multidisciplinary Analysis (AMMA) campaign, pointing to an insufficient observational constraint of the (re)analyses in other years. It is hoped that this work will raise awareness of the limited reliability of (re)analysis products over West Africa during the summer, particularly during northward surges of the ITD, and will instigate further work to improve their quality.

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Using Weather Forecasts to Help Manage Meningitis in the West African Sahel

Abstract: Integrating research, o p eration s, and c o m m u n ity engagem ent, a m u ltin a tio n a l and m ultidisciplinary te a m uses relative h u m id ity forecasts t o b e tte r manage m eningitis in th e Sahel.

Cited by 14 publications

References 38 publications

The local response of El Niño events and changing disease distribution in Tanzania

The local response of El Niño events and changing disease distribution in Tanzania

Relationship between meteorological variables/dust and the number of meningitis cases in Burkina Faso

Disagreements in Low-Level Moisture between (Re)Analyses over Summertime West Africa

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