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3 results on '"Kakembo, R."'

1. Inferring HIV-1 transmission networks and sources of epidemic spread in Africa with deep-sequence phylogenetic analysis

Author

Ratmann, O., Grabowski, M.K., Hall, M., Golubchik, T., Wymant, C., Abeler-Dörner, L., Bonsall, D., Hoppe, A., Brown, A.L., de Oliveira, T., Gall, A., Kellam, P., Pillay, D., Kagaayi, J., Kigozi, G., Quinn, T.C., Wawer, M.J., Laeyendecker, O., Serwadda, D., Gray, R.H., Fraser, C., Ayles, H., Bowden, R., Calvez, V., Cohen, M., Dennis, A., Essex, M., Fidler, S., Frampton, D., Hayes, R., Herbeck, J.T., Kaleebu, P., Kityo, C., Lingappa, J., Novitsky, V., Paton, N., Rambaut, A., Seeley, J., Ssemwanga, D., Tanser, F., Nakigozi, G., Ssekubugu, R., Nalugoda, F., Lutalo, T., Galiwango, R., Makumbi, F., Sewankambo, N.K., R. Tobian, A.A., Reynolds, S.J., Chang, L.W., Nabukalu, D., Ndyanabo, A., Ssekasanvu, J., Nakawooya, H., Nakukumba, J., Kigozi, G.N., Nantume, B.S., Resty, N., Kambasu, J., Nalugemwa, M., Nakabuye, R., Ssebanobe, L., Nankinga, J., Kayiira, A., Nanfuka, G., Ahimbisibwe, R., Tomusange, S., Galiwango, R.M., Kalibbali, S., Nakalanzi, M., Otobi, J.O., Ankunda, D., Ssembatya, J.L., Ssemanda, J.B., Kairania, R., Kato, E., Kisakye, A., Batte, J., Ludigo, J., Nampijja, A., Watya, S., Nehemia, K., Anyokot, M., Mwinike, J., Kibumba, G., Ssebowa, P., Mondo, G., Wasswa, F., Nantongo, A., Kakembo, R., Galiwango, J., Ssemango, G., Redd, A.D., Santelli, J., Kennedy, C.E., and Wagman, J.

Abstract

To prevent new infections with human immunodeficiency virus type 1 (HIV-1) in sub-Saharan Africa, UNAIDS recommends targeting interventions to populations that are at high risk of acquiring and passing on the virus. Yet it is often unclear who and where these ‘source’ populations are. Here we demonstrate how viral deep-sequencing can be used to reconstruct HIV-1 transmission networks and to infer the direction of transmission in these networks. We are able to deep-sequence virus from a large population-based sample of infected individuals in Rakai District, Uganda, reconstruct partial transmission networks, and infer the direction of transmission within them at an estimated error rate of 16.3% [8.8–28.3%]. With this error rate, deep-sequence phylogenetics cannot be used against individuals in legal contexts, but is sufficiently low for population-level inferences into the sources of epidemic spread. The technique presents new opportunities for characterizing source populations and for targeting of HIV-1 prevention interventions in Africa.

Published
2019

2. Inferring HIV-1 transmission networks and sources of epidemic spread in Africa with deep-sequence phylogenetic analysis

Author

Ratmann, O., Grabowski, M.K., Hall, M., Golubchik, T., Wymant, C., Abeler-Dörner, L., Bonsall, D., Hoppe, A., Brown, A.L., de Oliveira, T., Gall, A., Kellam, P., Pillay, D., Kagaayi, J., Kigozi, G., Quinn, T.C., Wawer, M.J., Laeyendecker, O., Serwadda, D., Gray, R.H., Fraser, C., Ayles, H., Bowden, R., Calvez, V., Cohen, M., Dennis, A., Essex, M., Fidler, S., Frampton, D., Hayes, R., Herbeck, J.T., Kaleebu, P., Kityo, C., Lingappa, J., Novitsky, V., Paton, N., Rambaut, A., Seeley, J., Ssemwanga, D., Tanser, F., Nakigozi, G., Ssekubugu, R., Nalugoda, F., Lutalo, T., Galiwango, R., Makumbi, F., Sewankambo, N.K., R. Tobian, A.A., Reynolds, S.J., Chang, L.W., Nabukalu, D., Ndyanabo, A., Ssekasanvu, J., Nakawooya, H., Nakukumba, J., Kigozi, G.N., Nantume, B.S., Resty, N., Kambasu, J., Nalugemwa, M., Nakabuye, R., Ssebanobe, L., Nankinga, J., Kayiira, A., Nanfuka, G., Ahimbisibwe, R., Tomusange, S., Galiwango, R.M., Kalibbali, S., Nakalanzi, M., Otobi, J.O., Ankunda, D., Ssembatya, J.L., Ssemanda, J.B., Kairania, R., Kato, E., Kisakye, A., Batte, J., Ludigo, J., Nampijja, A., Watya, S., Nehemia, K., Anyokot, M., Mwinike, J., Kibumba, G., Ssebowa, P., Mondo, G., Wasswa, F., Nantongo, A., Kakembo, R., Galiwango, J., Ssemango, G., Redd, A.D., Santelli, J., Kennedy, C.E., Wagman, J., Ratmann, O., Grabowski, M.K., Hall, M., Golubchik, T., Wymant, C., Abeler-Dörner, L., Bonsall, D., Hoppe, A., Brown, A.L., de Oliveira, T., Gall, A., Kellam, P., Pillay, D., Kagaayi, J., Kigozi, G., Quinn, T.C., Wawer, M.J., Laeyendecker, O., Serwadda, D., Gray, R.H., Fraser, C., Ayles, H., Bowden, R., Calvez, V., Cohen, M., Dennis, A., Essex, M., Fidler, S., Frampton, D., Hayes, R., Herbeck, J.T., Kaleebu, P., Kityo, C., Lingappa, J., Novitsky, V., Paton, N., Rambaut, A., Seeley, J., Ssemwanga, D., Tanser, F., Nakigozi, G., Ssekubugu, R., Nalugoda, F., Lutalo, T., Galiwango, R., Makumbi, F., Sewankambo, N.K., R. Tobian, A.A., Reynolds, S.J., Chang, L.W., Nabukalu, D., Ndyanabo, A., Ssekasanvu, J., Nakawooya, H., Nakukumba, J., Kigozi, G.N., Nantume, B.S., Resty, N., Kambasu, J., Nalugemwa, M., Nakabuye, R., Ssebanobe, L., Nankinga, J., Kayiira, A., Nanfuka, G., Ahimbisibwe, R., Tomusange, S., Galiwango, R.M., Kalibbali, S., Nakalanzi, M., Otobi, J.O., Ankunda, D., Ssembatya, J.L., Ssemanda, J.B., Kairania, R., Kato, E., Kisakye, A., Batte, J., Ludigo, J., Nampijja, A., Watya, S., Nehemia, K., Anyokot, M., Mwinike, J., Kibumba, G., Ssebowa, P., Mondo, G., Wasswa, F., Nantongo, A., Kakembo, R., Galiwango, J., Ssemango, G., Redd, A.D., Santelli, J., Kennedy, C.E., and Wagman, J.

Abstract

To prevent new infections with human immunodeficiency virus type 1 (HIV-1) in sub-Saharan Africa, UNAIDS recommends targeting interventions to populations that are at high risk of acquiring and passing on the virus. Yet it is often unclear who and where these ‘source’ populations are. Here we demonstrate how viral deep-sequencing can be used to reconstruct HIV-1 transmission networks and to infer the direction of transmission in these networks. We are able to deep-sequence virus from a large population-based sample of infected individuals in Rakai District, Uganda, reconstruct partial transmission networks, and infer the direction of transmission within them at an estimated error rate of 16.3% [8.8–28.3%]. With this error rate, deep-sequence phylogenetics cannot be used against individuals in legal contexts, but is sufficiently low for population-level inferences into the sources of epidemic spread. The technique presents new opportunities for characterizing source populations and for targeting of HIV-1 prevention interventions in Africa.

3. Trends in the Marginal Cost of Male Circumcision in Rural Rakai Uganda.

Author

Alfonso YN, Bishai D, Nantongo A, Kakembo R, Kobusinge S, Kacker S, Kigozi G, and Gray R

Subjects
Adolescent, Adult, Africa, Aged, Humans, Longitudinal Studies, Male, Middle Aged, Rural Population, Uganda, Young Adult, Circumcision, Male economics, Health Care Costs trends
Abstract

Introduction: Male circumcision (MC) is an effective intervention to reduce HIV acquisition in men in Africa. We conducted a cost analysis using longitudinal data on expenditures on services and community mobilization to estimate the marginal cost of MC over time and understand cost drivers during scale-up., Methods: We used a time series with monthly records from 2008 to 2013, for a total of 72 monthly observations, from the Rakai MC Program in Uganda. Generalized linear models were used to estimate the marginal cost of an MC procedure., Results: The marginal cost per MC in a mobile camp was $23 (P < 0.01) and in static facilities was $35 (P < 0.1). Major cost drivers included supplies in mobile camps with increasing numbers of surgeries, savings due to task shifting from physicians to clinical officers, and increased efficiency as personnel became more experienced., Conclusions: As scale-up continues, marginal costs may increase because of mobilization needed for less motivated late adopters, but improved efficiency could contain costs., Competing Interests: All authors state no conflict of interest

Published
2016
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